Authors Alan Shen, Xiaoguang Peng, Callum P. Bailey, Sameh Dardona, and W.K Anson explore new techniques in ‘3Dprinting of polymer-bonded magnets from highly concentrated, plate-like particle suspension.’ While magnets have been created previously via UV-assisted direct writing (UADW), there were challenges in the project due to limitations posed by particle types, loading, and viscosity levels. The authors modeled some of their work here after the Farris effect, in mixing particles of two different sizes and reducing viscosity.
3D printing magnets with polymer is increasing in popularity with researchers due to the minimal amount of tooling required, and lack of material waste. While use of the UADW method has been most successful thus far, the researchers for this study dispersed ferromagnetic particles (NdFeB) in a polymer binder, creating a paste to be extruded and then cured under UV light.
Performance is enhanced by increasing the magnetic powder to non-magnetic binder ratio, but there is the risk of particle jams and clogs.
“Further, the ink viscosity may also become too high to be printed, as limited by the printing pressure and flow instabilities,” state the researchers. “Physically, the increase of viscosity is caused by an increase in both the hydrodynamics interactions and particle-particle interactions as the particle loading increases. At exceedingly high particle loadings, particle-particle interactions become increasingly important.”
While printing with concentrated non-spherical particles can be challenging, the researchers aimed to understand more about particle size and structure in relation to suspension rheology. NdFeB powders were average in size, with a spherical diameter ranging from 5 to 200 μm. Particles with high aspect ratios align progressively along the shear plane as the shear rate increases, leading to reduction in viscosity and shear thinning.
(a)-(d) Scanning Electron Micrographs (SEM) of sieved melt-spun NdFeB particles having an average particle size, or equivalent spherical diameter, of 5, 20, 80, 200 μm, as determined by laser diffraction. (e) Particle size distribution of the sieved, melt-spun NdFeB particles. Solid lines are cumulative distribution.
“The resulting magnets have an intrinsic coercivity (Hci) of 9.30 kOe, a remanence (Br) of 5.88 kG, and an energy product ((BH)max) of 7.26 MGOe,” stated the researchers, adding that the corresponding values are the highest in the literature of 3D printed magnets.
The samples created for the research not only ‘rival’ magnets created through more conventional methods like casting, but they are versatile for creating parts with different structures, and both shape and topology that can be further optimized.
“Scientifically, the rheological data presented in this study provides the basis for understanding and modeling highly concentrated suspensions of non-spherical particles, which remains largely unexplored. Technologically, the magnetic performance of 3D printed magnets may be further improved through material formulations and process control,” concluded the researchers.
“Of particular interest is to explore the use of anisotropic magnetic particles and how to control their alignment through in-situ processing [41] or post-processing, which may lead to even stronger magnets as suggested by other authors,” concluded the researchers.
(a) Schematic diagram and (b) actual images of the UV-assisted direct write (UADW) process for printing a cubic-shaped magnet. The schematic is reproduced from the authors’ previous publication [1]. Reprinted with permission from Elsevier.
Top view (a, b) and side view (c, d) of magnets printed from unimodal and bimodal suspensions. In the bimodal case, a larger nozzle tip of 1.6 mm was used to accommodate for the larger particles present, whereas a 400-μm (dia.) tip was used for the unimodal case. In both cases, the surface profile was captured using white light interferometry with a scanned area of 0.7 mm × 0.5 mm on the top surface. The color bar shows the height variation following the horizontal lines drawn across the sample.
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