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Purpose The purpose of this study is to understand how printing parameters and subsequent annealing impacts porosity and crystallinity of 3D printed polylactic acid (PLA) and how these structural characteristics impact the printed material’s tensile strength in various build directions. Design/methodology/approach Two experimental studies were used, and samples with a flat vs upright print orientation were compared. The first experiment investigates a scan of printing parameters and annealing times and temperatures above the cold crystallization temperature ( T cc ) for PLA. The second experiment investigates annealing above and below T cc at multiple points over 12 h. Findings Annealing above T cc does not significantly impact the porosity but it does increase crystallinity. The increase in crystallinity does not contribute to an increase in strength, suggesting that co-crystallization across the weld does not occur. Atomic force microscopy (AFM) images show that weld interfaces between printed fibers are still visible after annealing above T cc , confirming the lack of co-crystallization. Annealing below T cc does not significantly impact porosity or crystallinity. However, there is an increase in tensile strength. AFM images show that annealing below T cc reduces thermal stresses that form at the interfaces during printing and slightly “heals” the as-printed interface resulting in an increase in tensile strength. Originality/value While annealing has been explored in the literature, it is unclear how it affects porosity, crystallinity and thermal stresses in fused filament fabrication PLA and how those factors contribute to mechanical properties. This study explains how co-crystallization across weld interfaces is necessary for crystallinity to increase strength and uses AFM as a technique to observe morphology at the weld. 

Thermal transport in polymer nanocomposites becomes dependent on the interfacial thermal conductance due to the ultra‐high density of the internal interfaces when the polymer and filler domains are intimately mixed at the nanoscale. However, there is a lack of experimental measurements that can link the thermal conductance across the interfaces to the chemistry and bonding between the polymer molecules and the glass surface. Characterizing the thermal properties of amorphous composites are a particular challenge as their low intrinsic thermal conductivity leads to poor measurement sensitivity of the interfacial thermal conductance. To address this issue here, polymers are confined in porous organosilicates with high interfacial densities, stable composite structure, and varying surface chemistries. The thermal conductivities and fracture energies of the composites are measured with frequency dependent time‐domain thermoreflectance (TDTR) and thin‐film fracture testing, respectively. Effective medium theory (EMT) along with finite element analysis (FEA) is then used to uniquely extract the thermal boundary conductance (TBC) from the measured thermal conductivity of the composites. Changes in TBC are then linked to the hydrogen bonding between the polymer and organosilicate as quantified by Fourier‐transform infrared (FTIR) and X‐ray photoelectron (XPS) spectroscopy. This platform for analysis is a new paradigm in the experimental investigation of heat flow across constituent domains.

 

An analysis is presented of the error propagation through a simplified contact model for atomic force microscopy (AFM) static force spectroscopy, one that is meant to be intuitive and pedagogically informative rather than maximally realistic. It is shown that an important dimensionless ratio appears in several critical locations in the closed form error equation, and that under common calibration methods there exists a ``magic'' ratio where an important class of systematic calibration errors cancel out completely. This argument is extended to more complex contact models and the presence of a magic ratio is demonstrated using real data. A method is shown to identify and operate at optimal conditions in commercial AFMs. Targeting this magic ratio provides a simple, comprehensive guideline for cantilever selection, system calibration, and imaging parameter selection.