화학공학소재연구정보센터
Polymer, Vol.152, 35-41, 2018
Interlayer diffusion of surface segregating additives to improve the isotropy of fused deposition modeling products
It is well known that 3D printed parts prepared by fused deposition modeling (FDM) exhibit large anisotropy of mechanical properties. For instance, the mechanical properties observed of samples printed orthogonal to the print bed (transverse) are significantly weaker than those printed parallel to the bed (longitudinal). This behavior is a result of poor interlayer adhesion from limited diffusion and entanglement of chains across the interlayer interface. To improve the diffusion and entanglement of adjacent layers, our group has implemented a process in which bimodal blends comprised of a parent, high molecular weight polymer blended with an identical but low molecular weight (LMW) polymer is utilized. These bimodal blends lead to significant enhancements in the mechanical properties of samples printed in the transverse orientation. Additionally, the moduli, regardless of print orientation, become nearly identical, indicating a more isotropic part. To more fully understand this behavior, we report the impact of LMW architectures on the improvement of structural properties of 3D printed parts. The decrease in anisotropy of mechanical properties of PLA bimodal blends containing 2-arm (linear), 3-arm and 4-arm PLA stars (M-w of arm- similar to 11 k) at loadings of 3, 10, and 15 mol% are tested under the same protocol as previous linear specimens. With the addition of just 3 mol% of each LMW additive, increases in the maximum stress from 15% to 100% are observed for samples printed in the transverse orientation. A significant improvement in layer adhesion and a significantly more isotropic part is thus realized, where the 3-arm star exhibits optimal performance. Interpretation of the data presented leads to the conclusion that this is true because the 3-arm star most efficiently diffuses to the inter-filament interface and entangles with the linear polymer. (C) 2018 Elsevier Ltd. All rights reserved.