ArticleMaterials (Basel, Switzerland)2026
Design and Optimization of Composite Thermal Insulation Layers for Mine Ecological Restoration Under Simulated Solar Radiation: Integrating Response Surface Screening with Gaussian Process Bayesian Optimization.
Article in Materials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Quantitative Prediction of Coal-Gangue Content Using Terahertz Time-Domain Spectroscopy and Physics-Informed Machine Learning.Materials (Basel, Switzerland) · 2026Article
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Authors and funding
7 authors.
Funding
Abstract
Thermal regulation of surface soil is critical for vegetation establishment in degraded mining environments, yet the systematic design of insulation layers tailored to mine restoration remains underdeveloped. Fifteen candidate thermal insulation materials from six categories were evaluated under simulated solar radiation, and a two-stage optimization framework was established. The first stage employed response surface methodology (RSM) for preliminary screening; the second used Gaussian process regression with Bayesian optimization (GPR-BO) for mixture refinement. RSM identified hollow glass microspheres as the strongest positive contributor and wood chips as the most detrimental component. The GPR-BO framework yielded an optimal formulation achieving
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Registered trials
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