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Highly efficient graphene-based circular ring metasurface absorber for photonics device component design using artificial intelligence optimization
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DOI：10.1016/j.mtadv.2026.100905.png)
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Abstract
En 中文
This research introduces an advanced solar thermal absorber configuration utilizing graphene-based metasurfaces combined with cylindrical resonators on a silicon dioxide platform. The proposed architecture delivers outstanding broadband thermal absorption across the solar spectrum (0.2–3 μm), attaining an average efficiency of 96.415%. Finite element analysis confirms multiple resonance peaks surpassing 99% efficiency, with absorption bandwidths extending up to 2500 nm and maintaining levels above 98%, with spectral performance distributed as 77.8% in the UV region, 95.5% in the visible range, 98.3% in the near-infrared, and a remarkable 99.943% in the mid-infrared. Examination of parametric investigations highlight the influence of resonator geometry, incident light angle, and graphene's chemical potential. With a compact thickness of just 1400 nm, the proposed thermal absorber outperforms many existing designs in terms of broadband efficiency and angular stability. Additionally, the integration of a deep learning neural network model ensures reliable predictive accuracy, demonstrated by consistently high R2 scores across various test scenarios. Altogether, the synergy of exceptional broadband thermal absorption, compact geometry, angular resilience, and machine learning integration establishes this solar absorber as a promising advancement in next-generation solar thermal energy harvesting technologies.
Keywords:
Intelligent
Thermal
Graphene
Metasurface
Solar absorber
Deep learning
Industrial heating
Solar thermal
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8
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1.4K
Citations:
4.2K
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