Correlation Between Microscale Magnetic Particle Distribution and Magnetic-Field-Responsive Performance of Three-Dimensional Printed Composites

[+] Author and Article Information
Lu Lu

Department of Mechanical and
Industrial Engineering,
University of Illinois at Chicago,
842 W Taylor Street, ERF 1076,
Chicago, IL 60607
e-mail: llu27@uic.edu

Erina Baynojir Joyee

Department of Mechanical and
Industrial Engineering,
University of Illinois at Chicago,
842 W Taylor Street, ERF 1076,
Chicago, IL 60607
e-mail: ejoyee2@uic.edu

Yayue Pan

Department of Mechanical and
Industrial Engineering,
University of Illinois at Chicago,
842 W Taylor Street, ERF 1076,
Chicago, IL 60607
e-mail: yayuepan@uic.edu

1Corresponding author.

Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MICRO- AND NANO-MANUFACTURING. Manuscript received June 17, 2017; final manuscript received November 20, 2017; published online December 14, 2017. Editor: Nicholas Fang.

J. Micro Nano-Manuf 6(1), 010904 (Dec 14, 2017) (8 pages) Paper No: JMNM-17-1038; doi: 10.1115/1.4038574 History: Received June 17, 2017; Revised November 20, 2017

To date, several additive manufacturing (AM) technologies have been developed for fabricating smart particle–polymer composites. Those techniques can control particle distributions to achieve gradient or heterogeneous properties and functions. Such manufacturing capability opened up new applications in many fields. However, it is still widely unknown how to design the localized material distribution to achieve desired product properties and functionalities. The correlation between microscale material distribution and macroscopic composite performance needs to be established. In our previous work, a novel magnetic field-assisted stereolithography (M-PSL) process was developed, for fabricating magnetic particle–polymer composites. In this work, we focused on the study of magnetic-field-responsive particle–polymer composite design with the aim of developing guidelines for predicting the magnetic-field-responsive properties of the composite. Microscale particle distribution parameters, including particle loading fraction, magnetic particle chain structure, microstructure orientation, and particle distribution patterns, were investigated. Their influences on the properties of particle–polymer liquid suspensions and properties of the three-dimensional (3D) printed composites were characterized. By utilizing the magnetic anisotropy properties of the printed composites, motions of the printed parts could be actuated at different positions in the applied magnetic field. Physical models were established to predict magnetic properties of the composite and trigger distance of fabricated parts. The predicted results agreed well with the experimental measurements, indicating the effectiveness of predicting macroscopic composite performance using microscale distribution data, and the feasibility of using the developed physical models to guide multimaterial and multifunctional composite design.

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Grahic Jump Location
Fig. 2

(a) and (b) A printed sample in set-0. (c) and (d) A printed sample in set-1. (e)–(h) Printed samples in set-2.

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Fig. 1

A schematic diagram of the smart polymer composite printing system using M-PSL process. (I) Resin vat (II) microscaled nozzle (III) particle droplet (IV) magnet (V) image unit (VI) platform (VII) linear actuator.

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Fig. 3

Cured single layer sample: (a) microscopic images and SEM images of cured thin pieces and (b) SEM of the chain structure

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Fig. 4

Shear stress–shear rate plot: (a) pure resin, (b) pure MR fluid, (c) suspension samples without magnetic field, and (d)suspension sample with magnetic field

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Fig. 5

Comparison between experimental data and prediction: (a) saturation magnetization and (b) trigger distance

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Fig. 6

Experimental trigger distance with different chain orientations

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Fig. 7

Magnetic flux density of samples in (a) set-0, (b) set-1, and (c) set-2



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