Soliman, M. orcid.org/0000-0003-2486-5933, Forbes, F. orcid.org/0009-0000-2128-475X and Damian, D.D. orcid.org/0000-0002-0595-0182 (2025) Yeast-driven and bioimpedance-sensitive biohybrid soft robots. Cyborg and Bionic Systems, 6. ISSN 2097-1087
Abstract
Biohybrid robots integrate biological components with synthetic materials to harness the unique capabilities of living systems for robotic functions. This study focuses on leveraging yeast fermentation dynamics to enable actuation and sensing in soft robotic systems. By leveraging yeast’s natural ability to produce carbon dioxide and generate pressure during fermentation, we demonstrate the feasibility of creating biohybrid robots with lifelike behavior and adaptability. Our research integrates bioimpedance sensing into track yeast behavior and metabolic dynamics in real time. We developed an adjustable single-resistor oscillator circuit by using a digital potentiometer to measure impedance frequency and model the yeast growth rate. Experimental results reveal the sensitivity of the single-resistor oscillator circuit to variations in yeast concentration and demonstrate the correlation between yeast behavior and actuation power. Furthermore, we highlight the potential of yeast-driven robots for various applications by demonstrating a yeast-driven soft limb capable of rotating 140° tested at different temperatures, an inflatable membrane actuator functioning as a tactile sensor detecting forces up to 4.5 N, a palpation probe for differentiating tissue stiffness, and a gripper capable of manipulating objects. This work lays the foundation for advancing biohybrid robotics by integrating yeast fermentation dynamics with bioimpedance sensing, enhancing the functionality of robotic systems.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2025 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 May 2025 08:48 |
Last Modified: | 08 May 2025 08:48 |
Published Version: | https://doi.org/10.34133/cbsystems.0233 |
Status: | Published |
Publisher: | American Association for the Advancement of Science (AAAS) |
Refereed: | Yes |
Identification Number: | 10.34133/cbsystems.0233 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:226085 |