Summary
Liquid flows in vascular networks are among the most effective ways to transport matter and information for life. Artificial vascular networks have mimicked this strategy without reproducing the same level of autonomy and adaptability. From animals to fungi, the most adaptable organisms control fluid transport with vessels that actively contract upon local sensing of stimuli. This adaptative fluid transport enables functionalities in organisms such as autonomous locomotion toward objectives. How are the orientation and rate of fluid flows controlled by self-contractions? How do these self-contracting networks tailor autonomous functionalities? So far, we do not know. Studies on organisms are limited to observations and lack the systematical characterizations required to apply these observations to artificial materials.
Self-Flow hypothesizes that artificial vascular networks containing distributed sensors and actuators can decipher how self-contractions enable adaptable fluid transport. From there, materials containing self-contracting artificial vascular networks will enable systematical studies on the emergence of autonomous functionalities. With this experimental asset reinforced by theoretical and numerical models, my group and I will address the following questions:
• Q1 DELIVER: How do self-contractions transport fluids across networks?
• Q2 ADAPT: How do self-contractions autonomously adapt to the need of the network?
• Q3 BEHAVE: How do self-contractions enable living matter functionalities?
Self-Flow will combine active matter and mechanistic approaches to model fluid transport in self-contracting vascular networks. I will use these results to design active vascularized materials that use fluid transfer to autonomously locomote towards objectives and exchange information with their pairs. This will open the way to autonomous robots that can change shape, split or recombine like soft materials and develop functionalities beyond locomotion.
Self-Flow hypothesizes that artificial vascular networks containing distributed sensors and actuators can decipher how self-contractions enable adaptable fluid transport. From there, materials containing self-contracting artificial vascular networks will enable systematical studies on the emergence of autonomous functionalities. With this experimental asset reinforced by theoretical and numerical models, my group and I will address the following questions:
• Q1 DELIVER: How do self-contractions transport fluids across networks?
• Q2 ADAPT: How do self-contractions autonomously adapt to the need of the network?
• Q3 BEHAVE: How do self-contractions enable living matter functionalities?
Self-Flow will combine active matter and mechanistic approaches to model fluid transport in self-contracting vascular networks. I will use these results to design active vascularized materials that use fluid transfer to autonomously locomote towards objectives and exchange information with their pairs. This will open the way to autonomous robots that can change shape, split or recombine like soft materials and develop functionalities beyond locomotion.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101117080 |
| Start date: | 01-11-2023 |
| End date: | 31-10-2028 |
| Total budget - Public funding: | 1 499 179,00 Euro - 1 499 179,00 Euro |
Cordis data
Original description
Liquid flows in vascular networks are among the most effective ways to transport matter and information for life. Artificial vascular networks have mimicked this strategy without reproducing the same level of autonomy and adaptability. From animals to fungi, the most adaptable organisms control fluid transport with vessels that actively contract upon local sensing of stimuli. This adaptative fluid transport enables functionalities in organisms such as autonomous locomotion toward objectives. How are the orientation and rate of fluid flows controlled by self-contractions? How do these self-contracting networks tailor autonomous functionalities? So far, we do not know. Studies on organisms are limited to observations and lack the systematical characterizations required to apply these observations to artificial materials.Self-Flow hypothesizes that artificial vascular networks containing distributed sensors and actuators can decipher how self-contractions enable adaptable fluid transport. From there, materials containing self-contracting artificial vascular networks will enable systematical studies on the emergence of autonomous functionalities. With this experimental asset reinforced by theoretical and numerical models, my group and I will address the following questions:
• Q1 DELIVER: How do self-contractions transport fluids across networks?
• Q2 ADAPT: How do self-contractions autonomously adapt to the need of the network?
• Q3 BEHAVE: How do self-contractions enable living matter functionalities?
Self-Flow will combine active matter and mechanistic approaches to model fluid transport in self-contracting vascular networks. I will use these results to design active vascularized materials that use fluid transfer to autonomously locomote towards objectives and exchange information with their pairs. This will open the way to autonomous robots that can change shape, split or recombine like soft materials and develop functionalities beyond locomotion.
Status
SIGNEDCall topic
ERC-2023-STGUpdate Date
12-03-2024
Images
No images available.
Geographical location(s)
Search
