Najam Taha, Vattathurvalappil Suhail Hyder, Haq Mahmoodul, Baluch Abrar H
Department of Aerospace Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
Interdisciplinary Research Center for Advanced Materials, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
Sci Rep. 2025 Aug 14;15(1):29776. doi: 10.1038/s41598-025-12964-x.
Electromagnetic induction technology enables rapid, noncontact heating of conductive polymer nanocomposites, yet uncontrolled localized heating during this process can induce significant thermomechanical damage. Key influencing factors include nanoparticle dispersion, agglomeration, magnetic field frequency, and coil geometry. This study presents a multiphysics computational model to simulate the induction heating of acrylonitrile butadiene styrene reinforced with iron oxide (FeO) nanoparticles, assessing the impact of these variables on heating efficiency. Numerical predictions were validated against experimental data at four FeO weight concentrations, demonstrating strong agreement and confirming a positive correlation between nanoparticle content and heating rate. Additionally, higher frequencies substantially enhanced heating, while nanoparticle agglomeration was found to promote localized overheating, posing a risk of material degradation. Although parameters such as particle size, coil design, and polymer positioning influenced heating rates, their effects were comparatively minor. The developed computational framework, experimentally validated, proves reliable and adaptable for modeling induction heating in diverse polymer nanocomposite systems.
电磁感应技术能够对导电聚合物纳米复合材料进行快速、非接触式加热，然而在此过程中不受控制的局部加热会导致显著的热机械损伤。关键影响因素包括纳米颗粒的分散、团聚、磁场频率和线圈几何形状。本研究提出了一个多物理场计算模型，用于模拟用氧化铁（FeO）纳米颗粒增强的丙烯腈-丁二烯-苯乙烯的感应加热，评估这些变量对加热效率的影响。针对四种FeO重量浓度的实验数据对数值预测进行了验证，结果显示出高度一致性，并证实了纳米颗粒含量与加热速率之间存在正相关。此外，更高的频率显著提高了加热效果，而发现纳米颗粒团聚促进了局部过热，存在材料降解的风险。尽管诸如颗粒尺寸、线圈设计和聚合物位置等参数会影响加热速率，但其影响相对较小。经过实验验证的所开发计算框架证明了其在模拟各种聚合物纳米复合材料系统中的感应加热方面的可靠性和适用性。
