ArticleScientific reports2025
Optimization of ultra-wideband metamaterial MXene-based polarization-insensitive solar absorber using machine learning for solar heater application.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Machine learning-assisted design of a wideband Fe-SiOScientific reports · 2026Article
- Deep learning-assisted ultrathin broadband vanadium dioxide-based polarization-insensitive terahertz metamaterial absorber.Scientific reports · 2026Article
- Accurate prediction of geometrical parameters of an ultra-broadband metamaterial absorber using machine learning.Scientific reports · 2025Article
- Metamaterial-Enhanced Solar-Driven Processes for Energy Conversion and Water Treatment.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim was to optimize energy production and minimize energy losses with regard to sources of sustainable energy, particularly solar energy, by examining a variety of solar absorber designs developed from various materials. Metamaterial MXene/W-based Resonator Solar Absorber (MMRSA) using MXene and Tungsten material utilized in a resonator, which has a tiny wire and cylindrical ring-shaped geometry. The MgF
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Registered trials
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