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Graphene-enhanced Cr-Ti-TiN broadband absorber for solar thermal systems: a computational and machine learning approach | Synapse
March 3, 2026
Graphene-enhanced Cr-Ti-TiN broadband absorber for solar thermal systems: a computational and machine learning approach
KA
Khaled Aliqab
Jouf University
BH
Bo Bo Han
AB
Ashish Baldania
Gujarat University
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Key Points
Improvement in absorption efficiency significantly enhances solar thermal systems.
Using computational methods, the study shows a 25% increase in absorption performance.
Utilizing machine learning techniques, the analysis identifies optimal material configurations for absorbers.
The findings suggest that graphene usage could revolutionize energy-efficient thermal applications.
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Aliqab et al. (Tue,) studied this question.
synapsesocial.com/papers/69a761bac6e9836116a2fc8c
https://doi.org/https://doi.org/10.1007/s10825-026-02516-5