Nanoparticle Sintering Model: Simulation and Calibration Against Experimental Data

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. Changes in relative density are then calculated from the results of the PFM simulations. These results are compared to experimental data obtained from furnace heating done on dried copper nanoparticle inks, and the simulation constants are calibrated to match physical properties.

Fusion of Stacked Nanowires: From Atomistic to Analytical Models

“…This is equivalent to ≈3 × 10 3 CPU hours for MD simulations and ≈1.5 × 10 −3 CPU hours for the analytical model, six orders of magnitude improvement in computational effort. Based on past work on phase-field modeling, [15][16][17] Monte Carlo simulations, [41] and cellular automata simulations [18] the computational effort of our model should still be lesser by a few orders of magnitude, although this needs to be tested by modeling NW fusion using these methods.…”

“…[13,14] Cellular automata, Monte Carlo, phase field, and discrete element methods may potentially be used to model neck growth in NW assemblies. [15][16][17][18] There is no work on modeling NW fusion using the first three methods, likely because the need for significant domain discretization significantly increases the computational cost. The discrete element method does not suffer from this issue since discretization of the entire domain is not needed.…”

An Aerosol Jet Printed Resistance Temperature Detector‐Micro Hotplate with Temperature Coefficient of Resistance Stabilized by Electrical Sintering

“…The nanoparticles do not melt and reform during sintering; instead, coalescence occurs by necking, a surface and grain diffusion phenomenon. [38] The grain boundaries can continue to grow by electromigration at high current, [39] leading to changes in resistance and TCR. Therefore, a thermally sintered RTD-μHP could function inaccurately at temperatures below its fully sintered temperature.…”