Here,
we present knittable shape-memory polymeric fibers extruded
using a 3D-printer nozzle-based melt-spinning method for high throughput
of composition and condition testing. These structures are used as
the basis for electroactive shape-changing knitted textiles combining
several types of fibers, including organic fibrous heaters. These
structures represent a different approach to “on-demand”
shape-memory fibers and can be incorporated into a variety of textile
architectures, including inlaid knitting, diagonal interlacements,
and a knit/purl design for an anisotropic knitted texture. The influence
of manufacturing process parameters (e.g., drawing ratio during melt-spinning)
on physical properties of the shape-memory fibers was measured using
X-ray diffraction, thermomechanical cycling, scanning electron microscopy,
and mechanical testing. The degree of crystallinity increased from
19.4 to 22.4% with the increased drawing ratio, with a maximum strain
% of 450 and the fibers being able to lift 457 times their own weight.
Further, we present a scalable strategy for bicomponent filament production,
in which two distinct polymers are melt-spun in a side-by-side configuration
and when actuated showed a coiled structure with different mechanical
and thermal behavior than pure SMP fibers. The knitted textiles, obtained
with a computer-controlled knitting machine able to produce 3D knitted
structures, are deformed from two-dimensional planar structures to
three-dimensional conformations by applying a voltage to the organic
fibrous heaters. The deformed structure can be fixed by removing the
applied voltage and can be returned to a planar configuration by heating
and applying an uniaxial stress. Therefore, a hierarchical approach
for fully textile-based, bendable, knittable, and electroactive soft
actuators is presented. The results presented here demonstrate lab-scale
production and high-throughput screening of advanced fibers with tunable
properties.