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Composites printed using material extrusion additive manufacturing (AM) typically exhibit alignment of high- aspect-ratio reinforcements parallel to the print direction. This alignment leads to highly anisotropic stiffness, strength, and transport properties. In many cases, it would be desirable to increase mechanical and transport properties transverse to the print direction, for example, in 3D-printed heat sinks or heat exchangers where heat must be moved efficiently between printed roads or layers. Rotational direct ink writing (RDIW), where the deposition nozzle simultaneously rotates and translates during deposition, provides a method to reorient fibers transverse to the print direction during the printing process. In the present work, carbon fiber-reinforced epoxy composites were printed by RDIW with a range of nozzle rotation rates and the in-plane and through-thickness thermal conductivity was measured. In addition, the orientation of carbon fiber (CF) in the composites was measured using optical microscopy and image analysis, from which second-order fiber orientation tensors were calculated. These results showed that the orientation of CF became less anisotropic as nozzle rotation rate increased, leading to increased through-thickness thermal conductivity, which increased by 40% at the highest rotation rate. The orientation tensors also showed that RDIW was more effective at reorienting fibers within the in-plane transverse direction compared to the through-thickness transverse direction. The results presented here demonstrate that a current weakness of material extrusion AM composites—poor thermal conductivity in the through-thickness direction—can be significantly improved with RDIW. 

The conservation field is experiencing a rapid increase in the amount, variety, and quality of spatial data that can help us understand species movement and landscape connectivity patterns. As interest grows in more dynamic representations of movement potential, modelers are often limited by the capacity of their analytic tools to handle these datasets. Technology developments in software and high-performance computing are rapidly emerging in many fields, but uptake within conservation may lag, as our tools or our choice of computing language can constrain our ability to keep pace. We recently updated Circuitscape, a widely used connectivity analysis tool developed by Brad McRae and Viral Shah, by implementing it in Julia, a high-performance computing language. In this initial re-code (Circuitscape 5.0) and later updates, we improved computational efficiency and parallelism, achieving major speed improvements, and enabling assessments across larger extents or with higher resolution data. Here, we reflect on the benefits to conservation of strengthening collaborations with computer scientists, and extract examples from a collection of 572 Circuitscape applications to illustrate how through a decade of repeated investment in the software, applications have been many, varied, and increasingly dynamic. Beyond empowering continued innovations in dynamic connectivity, we expect that faster run times will play an important role in facilitating co-production of connectivity assessments with stakeholders, increasing the likelihood that connectivity science will be incorporated in land use decisions.