Visualisation of conductive filler distributions in polymer composites using voltage and energy contrast imaging in SEM

Yanwen Liu, Xiaorong Zhou, James Carr, Colin Butler, Stephen L. Mills, Jason O'Connor, Eoghan McAlpine, Teruo Hashimoto, Xiangli Zhong, George E. Thompson, Geoff M. Scamans, Peter Howe, Michael A. McCool, Neil S. Malone

Research output: Contribution to journalArticlepeer-review

Abstract

Semiconductive composites have been examined using advanced scanning electron microscopy (SEM). For the first time, voltage contrast and energy contrast between the conductive filler and the polymer matrix have been revealed using a secondary electron detector placed inside the lens system and an energy selective backscattering detector respectively. Critical parameters, including loading level, distribution, dimension and shape of conductive fillers, correlating to the electrical conductivities of the composites, have been investigated and quantitatively determined. These parameters are essential for performance predictions, product quality control and new product development. The volume fractions of the conductive fillers in the two investigated composites were determined as 20.9% and 14.2% respectively. Higher frequency of distribution distance between the conductive filler aggregates within the ranges of 20-100 nm was revealed for the composite with volume fraction of 20.9%. The aggregates of conductive fillers showed mainly branched shapes. The information obtained provides further insight into the conductivity mechanism of conductive filler loaded polymer composite. © 2012 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)330-340
Number of pages11
JournalPolymer
Volume54
Issue number1
Early online date9 Nov 2012
DOIs
Publication statusPublished - 8 Jan 2013

Keywords

  • Conductive filler particles
  • Energy contrast
  • Voltage contrast imaging

Fingerprint

Dive into the research topics of 'Visualisation of conductive filler distributions in polymer composites using voltage and energy contrast imaging in SEM'. Together they form a unique fingerprint.

Cite this