Characterization and quantification of hierarchical particle microstructures in external field-processed composites

Dashiell Papula, Zoubeida Ounaies, Paris Von Lockette, Denise Widdowson, Anil Erol, Abdulla Masud

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this study, we discuss the characterization and quantification of composite microstructures formed by the external field manipulation of high aspect ratio magnetic particles in an elastomeric matrix. In our prior work, we have demonstrated that the simultaneous application of electric and magnetic fields on hard magnetic particles with geometric anisotropy can create a hierarchy of structures at different length scales, which can be used to achieve a wide range of properties. We aim to characterize these hierarchical structures and relate them to final composite properties so we can achieve our ultimate goal of designing a material for a prescribed performance. The complex particle structures are formed during processing by using electric and magnetic fields, and they are then locked-in by curing the polymer matrix around the particles. The model materials used in the study are barium hexaferrite (BHF) particles and polydimethylsiloxane (PDMS) elastomer. BHF was selected for its hard magnetic properties and high geometric anisotropy. PDMS was selected for its good mechanical properties and its tunable curing kinetics. The resulting BHF-PDMS composites are magnetoactive, i.e., they will deform and actuate in response to magnetic fields. In order to investigate the resulting particle orientation, distribution and alignment and to predict the composite's macro scale properties, we developed techniques to quantify the particle structures. The general framework we developed allows us to quantify and directly compare the microstructures created within the composites. To identify structures at the different length scales, images of the composite are taken using both optical microscopy and scanning electron microscopy. We then use ImageJ to analyze them and gather data on particle size, location, and orientation angle. The data is then exported to MATLAB, and is used to run a Minimum Spanning Tree Algorithm to classify the particle structures, and von Mises Distributions to quantify the alignment of said structures. Important findings show 1) the ability to control structure using a combination of external electric, magnetic and thermal fields; 2) that electric fields promote long range order while magnetic fields promote short-range order; and 3) the resulting hierarchical structure greatly influence bulk material properties. Manipulating particles in a composite material is technologically important because changes in microstructure can alter the properties of the bulk material. The multifield processing we investigate here can form the basis for next generation additive manufacturing platforms where desired properties are tailored locally through in-situ hierarchical control of particle arrangements.

Original languageEnglish (US)
Title of host publicationProceedings of ASME 2021 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2021
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791885499
DOIs
StatePublished - 2021
EventASME 2021 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2021 - Virtual, Online
Duration: Sep 14 2021Sep 15 2021

Publication series

NameProceedings of ASME 2021 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2021

Conference

ConferenceASME 2021 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2021
CityVirtual, Online
Period9/14/219/15/21

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Mechanics of Materials
  • Artificial Intelligence

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