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Nanoparticle Sintering Model, Simulation and Calibration Against Experimental Data

[+] Author Affiliations
Obehi G. Dibua, Anil Yuksel, Nilabh K. Roy, Michael Cullinan

University of Texas at Austin, Austin, TX

Chee S. Foong

NXP Semiconductors, Austin, TX

Paper No. MSEC2018-6383, pp. V001T01A025; 8 pages
doi:10.1115/MSEC2018-6383
From:
  • ASME 2018 13th International Manufacturing Science and Engineering Conference
  • Volume 1: Additive Manufacturing; Bio and Sustainable Manufacturing
  • College Station, Texas, USA, June 18–22, 2018
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 978-0-7918-5135-7
  • Copyright © 2018 by ASME

abstract

One of the limitations of commercially available metal Additive Manufacturing (AM) processes is the minimum feature size most processes can achieve. A proposed solution to bridge this gap is microscale selective laser sintering (μ-SLS). The advent of this process creates a need for models which are able to predict the structural properties of sintered parts. While there are currently a number of good SLS models, the majority of these models predict sintering as a melting process, which is accurate for microparticles. However, when particles tend to the nanoscale, sintering becomes a diffusion process dominated by grain boundary and surface diffusion between particles. As such, this paper presents an approach to model sintering by tracking the diffusion between nanoparticles on a bed scale. Phase Field Modeling (PFM) is used in this study to track the evolution of particles undergoing sintering. Part properties such as relative density, porosity, and shrinkage are then calculated from the results of the PFM simulations. These results are compared to experimental data gotten from a Thermogravimetric Analysis done on dried copper nanoparticle inks, and the simulation constants are calibrated to match physical properties.

Copyright © 2018 by ASME

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