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

Abstract

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. This study presents a green alternative by developing two-dimensional nanoparticle-enhanced phase change materials using biodegradable beeswax infused with reduced graphene oxide, graphene oxide, and Ti₃C₂T_x MXene nanoparticles at varying concentrations (0.1–0.5 wt.%), a sustainable and eco-friendly alternative to paraffin wax. Comprehensive material characterization confirmed the structural stability and chemical compatibility of the prepared composites. Experimental results demonstrated that the addition of nanoparticles increased the thermal conductivity by 21.9% (up to 0.278 W (m·K)⁻¹) while maintaining latent heat storage capacity within 6–18% of the base phase change materials values. Experimental findings of thermophysical properties, including thermal conductivity and viscosity, were used to train machine learning based regression models, yielding predictive accuracy levels up to 95%. Additionally, numerical simulations based on these models replicated the experimental results, providing a reliable framework for future predictions. A discontinuity estimation model was also developed to accurately predict thermal conductivity changes during phase transitions, achieving 98% accuracy compared with experimental data. Computational simulations validated against experimental data showed a strong correlation (<5% deviation), confirming heat transfer performance enhancements. Notably, the calculated Nusselt number demonstrated that beeswax-based nanoparticle-enhanced phase change materials exhibited thermal performance comparable to paraffin wax-based systems, as Nusselt number = 2.46 [paraffin wax] versus 2.47 [beeswax] for rGO, and Nusselt number = 2.36 [paraffin wax] versus 2.30 [beeswax] for Ti₃C₂T_x MXene, supporting its potential as a sustainable, biodegradable alternative. This integrated experimental-numerical approach supports the development of high-performance, eco-friendly nanoparticle-enhanced phase change materials, advancing sustainable thermal management solutions for next-generation cooling applications.

Keywords

2D materials / beeswax / machine learning / NePCM / thermal conductivity model / viscosity model

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2025 The Author(s). Energy & Environmental Materials published by John Wiley & Sons Australia, Ltd on behalf of Zhengzhou University.