journal article·2026-05Open access

Pellet Printing for Soft Robotic Devices

Yijia Wu, Ju‐Hung Chen, Ariana Olivares, Katherine Kostak, Stefan Pedicone, Savita V. Kendre, Markus P. Nemitz

Advanced Science· Volume 13· Issue 30

Abstract

ABSTRACT Rapid prototyping of soft robotic devices is often constrained by manual fabrication or additive manufacturing methods that are limited in material choice or require extensive post‐processing. Fused Granulate Fabrication offers a scalable alternative by extruding thermoplastic pellets through a screw‐based extruder, enabling continuous, high‐throughput printing and access to a broad range of commercially available materials, from rigid plastics to silicone‐soft elastomers with Shore hardness as low as 6A. Reliable 3D printing of airtight pneumatic soft structures at volumetric flow rates up to 5 mm 3 /s is demonstrated by addressing inconsistent extrusion and stringing issues through a combination of hardware optimization and a materials‐centered printing strategy. Extrusion and oozing tests are used to construct material‐specific oozing performance profiles, establishing practical guidelines for material selection in FGF printing, and are linked to key rheological descriptors. The mechanical performance of thermoplastic styrenic block copolymer pellets is characterized, revealing Mullins‐effect‐induced softening, and fabricated pneumatic actuators exhibit durability exceeding 100 000 bending cycles. Demonstrations include a pneumatically actuated robotic hand, a multi‐chamber robotic fish, and a soft pressure cuff. FGF enables the digital fabrication of large‐scale, airtight soft robotic devices using commercially available thermoplastic pellets, providing a versatile, cost‐effective, and scalable alternative to soft lithography with mechanical performance comparable to silicone elastomers.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Soft Robotics and Applications · Advanced Materials and Mechanics · Dielectric materials and actuators

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Mechanical Engineering Tufts University Medford USA

Funding

National Science Foundation

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