ArticleScientific reports2022
Graphene-based metasurface solar absorber design with absorption prediction using machine learning.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Machine learning-optimized graphene-integrated refractory metasurface for broadband solar energy harvesting.Scientific reports · 2026Article
- Machine-learning-assisted photonic device development: a multiscale approach from theory to characterization.Nanophotonics (Berlin, Germany) · 2025Review
- Optimization of ultra-wideband metamaterial MXene-based polarization-insensitive solar absorber using machine learning for solar heater application.Scientific reports · 2025Article
- Analysis of graphene coatings on various metallic/oxide crystal/composite material substrates using machine learning for enhanced solar thermal energy conversion.Scientific reports · 2025Article
- Nanostructures/TiN layer/AlScientific reports · 2024Article
- Efficient and high-quality absorption enhancement using epsilon-near-zero cylindrical nano-shells constructed by graphene.Scientific reports · 2024Article
- Article
- Broadband and Efficient Metamaterial Absorber Design Based on Gold-MgF2-Tungsten Hybrid Structure for Solar Thermal Application.Micromachines · 2023Article
- Broadband Plasmonic Metamaterial Optical Absorber for the Visible to Near-Infrared Region.Nanomaterials (Basel, Switzerland) · 2023Article
- Recent Advances in Reconfigurable Metasurfaces: Principle and Applications.Nanomaterials (Basel, Switzerland) · 2023Review
- Design and analysis of high-sensitivity tunable graphene sensors for cancer detection.Optical and quantum electronics · 2023Article
- Plasmonic Refractive Index and Temperature Sensor Based on Graphene and LiNbOSensors (Basel, Switzerland) · 2022Article
- Machine learning assisted metamaterial-based reconfigurable antenna for low-cost portable electronic devices.Scientific reports · 2022Article
- Ultra-broadband, wide-angle plus-shape slotted metamaterial solar absorber design with absorption forecasting using machine learning.Scientific reports · 2022Article
- Polarization Independent Metamaterial Absorber with Anti-Reflection Coating Nanoarchitectonics for Visible and Infrared Window Applications.Materials (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Solar absorber is required to absorb most of the energy of the solar spectral irradiance. We propose a graphene-based solar absorber design with two different metasurfaces to improve this absorption and increase the efficiency of the solar absorber. The metasurfaces are selected based on their symmetrical/asymmetrical nature (O-shape and L-shape). The O-shape metasurface design is showing better performance over the L-shape metasurface design. The absorption performance is also compared with AM 1.5 solar spectral irradiance to show the effectiveness of the solar absorber. The absorption values are also enhanced by varying the parameters like resonator thickness and substrate thickness. The proposed solar absorber design gives maximum absorption in the ultraviolet and visible range. Furthermore, the design is also showing a high and similar absorption rate over a wide angle of incidence. The absorption of O-shape metasurface design is also predicted using machine learning. 1D-Convolutional Neural Network Regression is used to develop a Machine Learning model to determine absorption values of intermediate wavelength for assorted values of angle of incidence, resonator thickness, and substrate thickness. The results of experiments reveal that absorption values may be predicted with a high degree of accuracy. The proposed absorber with its high absorbing capacity can be applied for green energy applications.
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Registered trials
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