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Graphene-Based Thermopneumatic Generator for On-Board Pressure Supply of Soft Robots.
- Source :
-
Soft robotics [Soft Robot] 2024 Sep 27. Date of Electronic Publication: 2024 Sep 27. - Publication Year :
- 2024
- Publisher :
- Ahead of Print
-
Abstract
- Various fields, including medical and human interaction robots, gain advantages from the development of bioinspired soft actuators. Many recently developed grippers are pneumatics that require external pressure supply systems, thereby limiting the autonomy of these robots. This necessitates the development of scalable and efficient on-board pressure generation systems. While conventional air compression systems are hard to miniaturize, thermopneumatic systems that joule heat a transducer material to generate pressure present a promising alternative. However, the transducer materials of previously reported thermopneumatic systems demonstrate high heat capacities and limited surface area resulting in long response times and low operation frequencies. This study presents a thermopneumatic pressure generator using aerographene, a highly porous (>99.99%) network of interconnected graphene microtubes, as lightweight and low heat capacity transducer material. An aerographene pressurizer module (AGPM) can pressurize a reservoir of 4.2 cm <superscript>3</superscript> to ∼14 kPa in 50 ms. Periodic operation of the AGPM for 10 s at 0.66 Hz can further increase the pressure in the reservoir to ∼36 kPa. It is demonstrated that multiple AGPMs can be operated parallelly or in series for improved performance. For example, three parallelly operated AGPMs can generate pressure pulses of ∼21.5 kPa. Connecting AGPMs in series increase the maximum pressure achievable by the system. It is shown that three AGPMs working in series can pressurize the reservoir to ∼200 kPa in about 2.5 min. The AGPM's minimalistic design can be easily adapted to circuit boards, making the concept a promising fit for the on-board pressure supply of soft robots.
Details
- Language :
- English
- ISSN :
- 2169-5180
- Database :
- MEDLINE
- Journal :
- Soft robotics
- Publication Type :
- Academic Journal
- Accession number :
- 39330933
- Full Text :
- https://doi.org/10.1089/soro.2023.0223