CHARACTERIZATION OF THE IN-PLANE AND CROSS-PLANE THERMAL CONDUCTIVITY OF POLYMER NANOFIBER THIN FILM UTILIZING THE 3-OMEGA METHOD [thesis]

John Carlin
The thermal conductivity of Polycaprolactone (PCL) nanofiber thin films produced via an electrospinning method has been studied using the 3ω method. The production process utilized to produce the nanofibers used in this work were selected from a range of tested production processes with preference given to process parameters that produced consistently sized polymer nanofibers, nanofibers devoid of defects, and parameters that increased the general alignment of the resulting PCL nanofiber thin
more » ... lm. The effect of the void portion of a PCL nanofiber thin film is observed with increasing void percentange inversely affecting the effective thermal conductivity of the nanofiber thin film in both the in-planer and crossplaner directions, but increasing the portion of heat energy conducted along the in-planer direction. The data in this work concludes the thermal conductivity of the nanofibers tested is 20% higher in the in-planer direction than in the cross-planer direction, with the highest recorded thermal conductivity being 4.82 W m −1 K −1 . ACKNOWLEDGMENTS I would like to express my very great appreciation to Professor Yi Zheng. During the entire duration of my masters degree, Professor Zheng was always willing and available to discuss the plans and results of my work as well as offer ideas and resources whenever I ran into problems. Prof. Zheng allowed me the final decision on the direction of all experiments and the freedom to organize my results. He has always encouraged deeper learning and was consistently willing to explore new ideas and concepts. Along with Prof. Zheng, I would like to also thank Professor Carl-Ernst Rousseau. Prof. Rousseau kindly stepped in to serve as my major professor when needed in the last month of my degree. He was always available to provide any administrative advice or assistance whenever needed.
doi:10.23860/thesis-carlin-john-2019 fatcat:kpiug3lgwfbt5a66msaglq7brq