Investigation of nanoparticle agglomeration on the effective thermal conductivity of a composite material. (June 2016)

• Record Type: Journal Article
• Authors: Wemhoff, Aaron P.; Webb, Anthony J.
• Is Part Of: International journal of heat and mass transfer. Volume 97(2016:Jun.)
• Page Start: 432
• Page End: 438
• Publication Date: 2016-06
• Subjects: Thermal conductivity -- Thermal boundary resistance -- Percolation; Heat -- Transmission -- Periodicals; Mass transfer -- Periodicals; Chaleur -- Transmission -- Périodiques; Transfert de masse -- Périodiques; Electronic journals; 621.4022
• DOI: 10.1016/j.ijheatmasstransfer.2016.02.027
• Languages: English
• ISSNs: 0017-9310

Abstract

Highlights: Inclusion agglomeration effects on bulk thermal conductivity are analyzed. Theory and finite element analysis are used to predict agglomeration effects. Spherical clustering is predicted to always reduce the bulk thermal conductivity. Linear agglomeration may mitigate or enhance the bulk thermal conductivity. Kapitza resistances dictate how linear agglomeration affects thermal conductivity. Abstract: The viability of organic phase change materials (PCMs), such as paraffin wax, for passive thermal management of portable electronics improves if the PCM overall bulk thermal conductivity is increased through the addition of highly conducting nanoparticles. Previous work has suggested the possibility of increasing the bulk thermal conductivity of composite materials through the controlled agglomeration of nanoparticles, yet no theoretical study has been performed to investigate the conditions under which the bulk thermal conductivity enhancement is achieved. Therefore, this study examines the influence of both spherical clustering and linear percolation network formation on the resultant bulk conductivity. This approach uses effective medium and percolation theories for unpercolated and percolated areas, respectively. Theoretical approaches are shown for spherical clustering and a 1-d conduction model of linear percolation networks, and finite element analysis (FEA) is used for a 2-d conduction model of linear percolation networks. The results for herringbone graphite nanofibers (HGNFs) in a paraffin matrix suggest that spherical clustering and linear agglomeration tend to reduce the bulk thermal conductivity, which agrees with experimental observations. However, linear percolation networks may enhance the effective thermal conductivity when large inclusion–matrix to inclusion–inclusion Kapitza resistance ratios are used.