首页|期刊导航|Energy & Environmental Materials|Tailoring Thermophysical Properties and Multiscale Machine Learning Modeling of 2D Nanomaterial-Infused Beeswax as a Green NePCM for Sustainable Thermal Management Systems

Tailoring Thermophysical Properties and Multiscale Machine Learning Modeling of 2D Nanomaterial-Infused Beeswax as a Green NePCM for Sustainable Thermal Management SystemsOA

中文摘要

Two-dimensional nanoparticle-enhanced phase change materials are transforming thermal management by improving thermal conductivity and heat transfer efficiency, offering efficient and sustainable cooling solutions than conventional hydrocarbon-based phase change materials. However, the environmental concerns necessitate the development of eco-friendly and green alternatives.

Abdullah Aziz;Shoaib Anwer;Eiyad Abu-Nada;Anas Alazzam

Department of Mechanical&Nuclear Engineering,Khalifa University of Science and Technology,Abu Dhabi 127788,UAE System on Chip Lab,Khalifa University,Abu Dhabi 127788,UAEDepartment of Mechanical&Nuclear Engineering,Khalifa University of Science and Technology,Abu Dhabi 127788,UAEDepartment of Mechanical&Nuclear Engineering,Khalifa University of Science and Technology,Abu Dhabi 127788,UAEDepartment of Mechanical&Nuclear Engineering,Khalifa University of Science and Technology,Abu Dhabi 127788,UAE System on Chip Lab,Khalifa University,Abu Dhabi 127788,UAE

通用工业技术

2D materialsbeeswaxmachine learningNePCMthermal conductivity modelviscosity model

《Energy & Environmental Materials》 2026 (3)

P.440-454,15

supported by Khalifa University competitive research award,RIG-2023-045,under Grant No.8474000553.

10.1002/eem2.70194

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