Experimental and explainable machine learning approach on thermal conductivity and viscosity of water based graphene oxide based mono and hybrid nanofluids

• 主要な著者: Kanti P.K., Paramasivam P., Wanatasanappan V.V., Dhanasekaran S., Sharma P.
• その他の著者: 57216493630
• フォーマット: 論文
• 出版事項: Nature Research 2025
• 主題: graphene oxide; nanofluid; silicon dioxide; article; controlled study; decision tree; explainable machine learning; game; hybrid; machine learning; pharmaceutics; prediction; random forest; temperature; thermal conductivity; viscosity; water

This study explores the thermal conductivity and viscosity of water-based nanofluids containing silicon dioxide, graphene oxide, titanium dioxide, and their hybrids across various concentrations (0 to 1 vol%) and temperatures (30 to 60��C). The nanofluids, characterized using multiple methods, exhib...