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.

The pesticide is any substance used to prohibit, destroy, or control pests, such as insects, fungus, rodents or, undesirable plant species that cause damage during crop production and storage. There are a lot of traditional methods to detect pesticides, among them gas chromatography (GC), high-performance liquid chromatography (HPLC), and their combinations with ultraviolet (UV) or mass spectroscopy. Nevertheless, these conventional techniques have several limitations, involving complicated pre-treatment steps, requiring expensive instruments, operational difficulty, lack of instrument portability, and difficulties in real-time monitoring. Surface-enhanced Raman spectroscopy (SERS) is one of the current leading techniques widely applied for the ultrasensitive detection of pesticides molecules. SERS takes advantage to combine the high specificity of Raman scattering with the signal amplification of electromagnetic enhancement provided by the excitation of surface Plasmon resonances in metallic nanostructures, together with the charge transfer mechanisms established between metal surfaces and analytes. In this brief review, types of classification of pesticides that can be classed have been reported. These classifications can provide valuable information on the chemistry of pesticides. The state of art of SERS, including a theoretical background study, is briefly described. Finally, some recent development and applications of optical and analytical techniques for pesticides detection have been summarized; a particular study will be focused on SERS combined with microfluidic technology that has appeared as advanced tools for surface enhanced Raman spectroscopy (SERS). They have been demonstrated to be interesting for in situ and real-time detection of analytes at extremely low concentrations.

We utilized density functional theory (DFT) to investigate the electronic structure and Raman spectrum of Azinphos-methyl (AzM) (C₁₀H₁₂N₃O₃PS₂) both in isolation and in combination with gold nanoclusters (Au_n, n = 2, 4, and 6). The research highlights a significant enhancement in Raman activity with increasing gold atom count from AzM-Au₂ to AzM-Au₄. The DFT calculations provide a comprehensive analysis of various electronic properties, including HOMO and LUMO energies, gap energy (Eg), ionization potential (IP), and electron affinity (EA), comparing these with experimental results from Liu et al. (2012). We also examined reactivity parameters, electrostatic properties, molecular electrostatic potential (MEP), Natural bond orbital (NBO) analysis, and atoms-in-molecules theory (AIM). The binding energy trends among the (AzM)-Aun complexes revealed a hierarchy: (AzM)-Au₂ > (AzM)-Au₆ > (AzM)-Au₄. Monte Carlo simulations were used to explore AzM interactions with gold nanoparticles (AuNPs) of various shapes and sizes, indicating that increased Raman intensity correlates with higher global electrophilicity and total polarizability. The results suggested that the stability of the complexes improves with more gold atoms, as evidenced by greater charge transfer, interaction energies, and second-order stabilization energies (E²). Among the complexes studied, AzM-Au₂ showed the highest stability. Monte Carlo simulations revealed that the right circular cone-shaped structure, especially at 7 nm, demonstrated the most negative adsorption energy, indicating stronger adsorption interactions. This research fills a gap in previous studies on AzM, providing valuable insights and serving as a reference for future work.

Background The objective of this study is to explore the potential of oxazole (C 3H 3NO), a fascinating heterocyclic compound naturally present, which is a potential ligand in the construction of Metal-Organic Frameworks (MOFs) for the selective capture of CO 2 in a nitrogen-rich atmosphere, using both molecular and solid-state simulation techniques. Methods This study investigates the equilibrium structures and binding energies of van der Waals aggregates formed by an oxazole molecule with nonpolar molecules such as CO 2 and N 2, considering both two-body systems (oxazole@CO 2 and oxazole@N 2) and three-body systems (oxazole@CO 2@N 2 and oxazole-CO 2/N 2@Au 6/Cu 6/Zn 3O 3). Molecular computations for these systems are conducted using ab initio calculations at the MP2/aug-cc-pVXZ level of theory, where X = (D, T). Additionally, solid-state simulations analyze the adsorption behaviors and energies of oxazole@CO 2 and oxazole@N 2 on metallic surfaces:Au, Cu and ZnO(111) through Monte Carlo methods. Results We find that the oxazole exhibits more adsorption selectivity for CO 2 than for N 2. Adding a second gas to the most stable complexes, oxazole@CO 2 and oxazole@N 2, the oxazole capture ability does not vary. On the contrary, it strengthens the adsorption energy of three-body complexes compared to two-body complexes. The addition of metallic clusters (Au 6, Cu 6, Zn 3O 3) and metallic surfaces (Au, Cu, ZnO) enhances the adsorption capacity, where Cu 6 is particularly efficient. Both ZnO and Cu surfaces offer significant adsorption advantages while remaining economically feasible. Conclusions This study demonstrates that oxazole exhibits a strong selectivity for CO 2 over N 2, with the addition of metallic clusters and surfaces significantly enhancing its adsorption capacity. These findings highlight the potential of oxazole-based materials for effective gas capture and separation, with positive implications for environmental sustainability.

In this work, Surface-Enhanced Raman Spectroscopy (SERS) was employed as an effective detection technique for folpet, characterized by its notable specificity and sensitivity. The investigation involved the use of UV–Vis, Raman, and SERS spectroscopy of folpet at different concentrations for a comprehensive study of plasmon-driven effects such as plasmon resonance, plasmon hybridization, and electric field enhancement resulting in the SERS’ intensification. Specifically, SERS detection of folpet solutions at concentrations below 100 µM is presented in detail by using Ag nanoparticles prepared with hydroxylamine reduction. The experimentation encompassed diverse conditions to optimize the detection process, with Raman spectra acquired for both folpet powder and aqueous solution of folpet at the natural pH. SERS analyses were conducted across a concentration range of 9.5 × 10⁻⁸ to 1.61 × 10⁻⁴ M, employing 532 nm excitation. The differences in the spectral profiles observed for folpet Raman powder and SERS are ascribed to N–S cleavage; these changes are attributed to plasmon catalysis induced by the used Ag nanoparticles. Transmission electron microscopy (TEM) was also important in the present analysis to better understand which mechanism of nanoparticles aggregation is more favorable for the SERS detection regarding the formation of hot spots in the suspension. Complementing the experimental data, the molecular structure and theoretical Raman spectra of the folpet molecule were calculated through density functional theory (DFT) methods. The outcomes of these calculations were crucial in the elucidation of folpet’s vibrational modes. The culmination of this research resulted in the successful detection of folpet, achieving a notable limit of detection at 4.78 × 10⁻⁸ M. This comprehensive approach amalgamates experimental and theoretical methodologies, offering significant insights into the detection capabilities and molecular characteristics of folpet via SERS analysis.