One of the challenges to rapidly manufacturing flexible electronics is the complexity involved in printing circuitry from stretchable conductors. Eutectic gallium alloys are typically used as the conductive material because they have unique high conductivity, self‐healing, and stretchable properties. However, limited 3D printing has been demonstrated by leveraging the structural stabilization provided by the thin gallium oxide film. Vertical structures are difficult to print with a liquid metal (LM) due to the low viscosity and high surface tension of the gallium alloy, which easily leads to coalescence. A method is presented to alter the physical structure of the liquid metal through the incorporation of a conductive nano‐ or micronickel fillers. The resulting rheological modification of the liquid metal to a paste drastically increases the fluidic elastic modulus and yield stress, rendering it 3D printable. Further, the modification retains the high electrical conductivity (3.9 × 106 ± 9.5 × 105 S m−1) and stretchability (over 350% strain) of pure liquid metal. The ability to print 3D standing structures using this highly conductive metal paste opens up new opportunities to manufacture more complex stretchable electronics.

How is information extracted from familiar and unfamiliar faces? Three experiments, in which eye-movement measures were used, examined whether there was differential sampling of the internal face region according to familiarity. Experiment 1 used a face familiarity task and found that whilst the majority of fixations fell within the internal region, there were no differences in the sampling of this region according to familiarity. Experiment 2 replicated these findings, using a standard recognition memory paradigm. The third experiment employed a matching task, and once again found that the majority of fixations fell within the internal region. Additionally, this experiment found that there was more sampling of the internal region when faces were familiar compared with when they were unfamiliar. The use of eye fixation measures affirms the importance of internal facial features in the recognition of familiar faces compared with unfamiliar faces, but only when viewers compare pairs of faces.

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Soft robots are designed to utilize their compliance and contortionistic abilities to both interact safely with their environment and move through it in ways a rigid robot cannot. To more completely achieve this, the robot should be made of as many soft components as possible. Here we present a completely soft hydraulic control valve consisting of a 3D-printed photopolymer body with electrorheological (ER) fluid as a working fluid and gallium-indium-tin liquid metal alloy as electrodes. This soft 3D-printed ER valve weighs less than 10 g and allows for onboard actuation control, furthering the goal of an entirely soft controllable robot. The soft ER valve pressure-holding capabilities were tested under unstrained conditions, cyclic valve activation, and the strained conditions of bending, twisting, stretching, and indentation. It was found that the max holding pressure of the valve when 5 kV was applied across the electrodes was 264 kPa, and that the holding pressure deviated less than 15% from the unstrained max holding pressure under all strain conditions except for indentation, which had a 60% max pressure increase. In addition, a soft octopus-like robot was designed, 3D printed, and assembled, and a soft ER valve was used to stop the fluid flow, build pressure in the robot, and actuate six tentacle-like soft bending actuators.