journal article·2026-04-01Open access

Scaling-associated aspects of liquid–gas phase change actuators in robots and wearable technologies

Rafal Ziembicki, Mathias Wendner, Ingrid Graz

Smart Materials and Structures· Volume 35· Issue 4

Abstract

Abstract Despite the increasing interest in phase change actuators for soft robotics and wearables, a systematic understanding of how their performance changes with size is still missing. Most existing designs are scaled empirically, without clear validation of whether force output, response time, and efficiency scale predictably with geometry. In this study, we investigate the scalability in size of PCAs by experimentally comparing actuator diameters ranging from 7 to 28 mm, targeting dimensions relevant for wearable and compact robotic applications. We analyze the influence of actuator size on response time, force generation, and mechanical output using different working fluids and heating power configurations. Our approach is based on the hypothesis that power input and actuation force should scale proportionally with liquid volume and surface area to allow for an equitable comparison. Accordingly, we evaluate whether two reduced-size actuators, each operating at half the volume and half the power, can collectively reproduce the performance of a single larger actuator. Our results reveal distinct scaling-related trade-offs between actuation speed and force efficiency, enabling a direct and quantitative comparison across sizes. Based on these findings, we introduce a compact PCA-based pumping concept and demonstrate its applicability in untethered McKibben muscles, worm-like robots, and wearable systems. This work provides a structured framework for the size-optimized design of liquid–gas phase change actuators and supports their integration into miniaturized soft robotic and assistive technologies.
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Research context

OpenAlex topics: Soft Robotics and Applications · Advanced Sensor and Energy Harvesting Materials · Dielectric materials and actuators

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

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