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Binder Jetting (BJ) is a low-cost Additive Manufacturing (AM) process that uses inkjet technology to selectively bind particles in a powder bed. BJ relies on the ability to control, not only the placement of binder on the surface but also its imbibition into the powder bed. This is a complex process in which picoliter-sized droplets impact powder beds at velocities of 1–10 m/s. However, the effects of printing parameters such as droplet velocity, size, spacing, and inter-arrival time on saturation level (fraction of pore space filled with binder) and line formation (merging of droplets to form a line) are unknown. Prior attempts to predict saturation levels with simple measurements of droplet primitives and capillary pressure assume that droplet/powder interactions are dominated by static equilibrium and neglect the impact of printing parameters. This study analyzes the influence of these parameters on the effective saturation level and conditions for line formation when printing single lines into powder beds of varied materials (316 stainless steel, 420 stainless steel, and alumina) and varied particle size (d50=10–47 µm). Results show that increasing droplet velocity or droplet spacing decreases effective saturation while droplet spacing, velocity, and inter-arrival time affect line formation. At constant printing velocity, the conditions for successful line printing are shown to be a function of droplet spacing and square root of the droplet inter-arrival time analogous to the Washburn model for infiltration into a porous media. The results have implications to maximizing build rates and improving quality of small features in BJ. 

Context: An Optimizing Performance through Intrinsic Motivation and Attention for Learning theory-based motor learning intervention delivering autonomy support and enhanced expectancies (EE) shows promise for reducing cognitive-motor dual-task costs, or the relative difference in primary task performance when completed with and without a secondary cognitive task, that facilitate adaptive injury-resistant movement response. The current pilot study sought to determine the effectiveness of an autonomy support versus an EE-enhanced virtual reality motor learning intervention to reduce dual-task costs during single-leg balance. Design: Within-subjects 3 × 3 trial. Methods: Twenty-one male and 24 female participants, between the ages of 18 and 30 years, with no history of concussion, vertigo, lower-extremity surgery, or lower-extremity injuries the previous 6 months, were recruited for training sessions on consecutive days. Training consisted of 5 × 8 single-leg squats on each leg, during which all participants mimicked an avatar through virtual reality goggles. The autonomy support group chose an avatar color, and the EE group received positive kinematic biofeedback. Baseline, immediate, and delayed retention testing consisted of single-leg balancing under single- and dual-task conditions. Mixed-model analysis of variances compared dual-task costs for center of pressure velocity and SD between groups on each limb. Results: On the right side, dual-task costs for anterior–posterior center of pressure mean and SD were reduced in the EE group (mean Δ = −51.40, Cohen d  = 0.80 and SD Δ = −66.00%, Cohen d  = 0.88) compared with the control group (mean Δ = −22.09, Cohen d  = 0.33 and SD Δ = −36.10%, Cohen d  = 0.68) from baseline to immediate retention. Conclusions: These findings indicate that EE strategies that can be easily implemented in a clinic or sport setting may be superior to task-irrelevant AS approaches for influencing injury-resistant movement adaptations.