Publications Internationales

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    Predicting the viscosity of hydrogen – methane blends at high pressure for hydrogen transportation and geo-storage: Integration of robust white-box machine learning frameworks
    (Elsevier, 2025) Alatefi, Saad; Youcefi, Mohamed Riad; Amar, Menad Nait; Djema, Hakim
    The integration of hydrogen into underground storage systems is pivotal for large-scale energy management, often involving blends with methane to leverage existing infrastructure. Accurate viscosity prediction of hydrogen – methane blends under subsurface conditions is essential for optimizing flow assurance and operational safety. Accordingly, this study employs three data-driven models, namely Genetic Expression Programming (GEP), Group Method of Data Handling (GMDH), and Multi-Gene Genetic Programming (MGGP), to predict the viscosity of hydrogen – methane mixtures for transportation and underground storage applications. A comprehensive dataset of 313 experimentally measured values from the literature were utilized to develop and validate the established correlations. The MGGP paradigm emerged as the top performer, achieving a root mean square error (RMSE) of 0.4054 and an R2 value of 0.9940, outperforming both GEP and GMDH, as well as prior predictive models. The consistency of the dataset was confirmed using the Leverage approach, ensuring robust predictions. In addition, the Shapley Additive Explanations technique revealed key factors influencing the viscosity predictions, enhancing the interpretability of the best-performing correlation. Furthermore, comparative trend analysis demonstrated the MGGP correlation's superior accuracy and robustness across varying blend compositions and operational conditions. These findings offer a reliable and simple-to-use predictive correlation for engineers and researchers designing hydrogen transport and storage systems, supporting efficient energy storage and the transition to a low-carbon economy
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    LeTID Mitigation by Electrical Injection Regeneration of Cz-Si and mc-Si BSF Silicon Solar Cells
    (Springer, 2024) Zentar, Imad Yacine; Bouhafs, Djoudi; Amrouch, Abdelhakim
    In this investigation, we provide further insight into the kinetics of light- and elevated-temperature-induced degradation (LeTID) by examining the impact of electrical injection regeneration on the development and subsequent mitigation of LeTID in boron-doped Czochralski silicon (Cz-Si) and multi-crystalline silicon (mc-Si) back-surface-field (BSF) solar cells. Electrical injection regeneration was applied to both Cz-Si and mc-Si solar cells with an injection current of 3 A at varying temperatures (180–200°C) for 20 min. The LeTID cycle was conducted at 75°C with an illumination intensity of 750 W/m2. A solar simulator was used to measure the current–voltage (I–V) characteristics of the cells. Our findings indicate that the LeTID regeneration process is influenced by both carrier injection and temperature. Notably, cells regenerated with an injection current of 3 A at 180°C for 20 min exhibited a reduction in degradation after extended light exposure under LeTID conditions. Specifically, mc-Si solar cells showed an efficiency degradation decrease of up to 3%, while Cz-Si cells displayed a similar reduction, compared to their initial values. These results highlight the enhanced anti-LeTID effects achieved through the regeneration process. Additionally, our study reveals that hydrogen and oxygen play roles in the formation and neutralization of defects associated with metallic impurities, distinct from boron-related defects. This insight contributes to understanding the complex mechanisms affecting the performance of these solar cells under various conditions.
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    Photoelectrochemical characterization of nano-crednerite AgMnO2 synthesized by Auto-Ignition : a novel Pphotocatalyst for H2 evolution
    (Springer, 2022) Koriche, N.; Brahimi, R.; Bellal, B.; Trari, M.
    AgMnO2 nanocrystallites (31 nm) were prepared by sol-gel auto-ignition at 400°C in air. The crednerite characterized by X-ray diffraction (XRD) showed a single phase, crystallizing in a monoclinic unit cell (SG: C2/m). The refinement was made by isotypy with CuMnO2. The oxide is a narrow band-gap semiconductor with an indirect transition at 1.43 eV. The electrical conduction occurs predominantly by small polaron hopping between mixed valences Ag2+/+ in the (a, b) planes with an activation energy of 0.35 eV. The density of holes (NA = 2 × 1015 cm–3) and their mobility (μh = 0.8 × 10–4 m–2 V–1 s–1) indicate a conduction being thermally activated. The oxygen insertion in the layered crystal lattice induces p-type conductivity, a fact confirmed by the electrochemical measurements. The flat band potential (Efb = –0.04 V) indicates a cationic character of both valence and conduction bands deriving mostly from Ag+ 4d-orbital. The electrochemical impedance spectroscopy shows the predominance of the bulk contribution followed by diffusion of O2– species. The energetic band diagram of AgMnO2 established from the photoelectrochemical study, predicts a spontaneous hydrogen formation; a rate evolution of 39 µmol g–1 min–1 and a power conversion of 0.37% were obtained under visible light irradiation (27 mW cm–2)