Machine learning-enhanced ultrawideband Al-In₂Se₃-AlN solar absorber investigation for heating water systems using thin-layer graphene

Shobhit K. Patel, Bo Bo Han, Osamah Alsalman and Om Prakash Kumar

Renewable Energy, 2025, vol. 243, issue C

Abstract: With the perfect absorption of the constructed structure in building a solar absorber, it can achieve the role of solar energy (green energy system). In constructing the perfect solar design, the applied material types and the number of layers need to be considered. Some additional layers of MXene, graphene, and so on can also be used to produce an ideal type of solar structure. In the current contributed solar design, a three-layer and a graphene performance combination with the materials of Aluminium (Al) for the resonator, the substrate material is Indium (III) selenide (In2Se3), and the whole structure is based on the Aluminium nitride (AlN). The wavelengths of 530 and 650 nm produce above 95 % absorption rates of 95.56 % and 95.29 % and the wide wavelength of 2800 nm generates 91.91 % as the current work's outputs. The results (absorption rates) on the descriptive parametric number can be generated by the applied ML (machine learning). In some thermal processes of the domestic sector, mandatory uses, non-commercial sectors, and generating steam and heating of oil systems can be performed with the current displayed solar design.

Keywords: Machine learning; Thermal system; Water heating; Multilayer; Graphene; Solar absorption; In2Se3; Wide-band structure (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:243:y:2025:i:c:s0960148125001752

DOI: 10.1016/j.renene.2025.122513

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