Meta-SMART Meta-stable Smart Metamaterials for Actively-controlled and Reversible Transition waves

Summary

Mechanical metamaterials play a crucial role in various applications, such as shape morphing, soft robotics, and logic elements. However, the control and guidance of transition waves within these materials have primarily been static. The Meta-SMART project aims to revolutionize this by actively controlling and guiding transition waves using piezoelectric and shape memory polymer-based multimaterial active switches integrated into metamaterial unit cells. Unlike traditional methods, Meta-SMART offers dynamic and reversible control, allowing the metamaterials to adapt autonomously and universally.
To optimize these smart metamaterials, we will implement a machine learning-based inverse design strategy to determine their geometrical parameters. Fabrication will involve 3D printing, followed by experimental testing of transition wave control and guidance. This innovation promises to advance the industrial applications of mechanical metamaterials, offering adaptability to external forces and desired outcomes. Potential uses include controlled energy absorption and dissipation for airflow control in aircraft, selective energy absorption in protective surfaces, and even treatment of Parkinson’s disease.
The Meta-SMART project represents a valuable opportunity to expand my expertise in smart materials and structures, enhancing my research profile through hands-on experience in testing and fabrication. Training activities such as TU Delft's teachers' training program, workshops on supervising research projects, and advanced courses in machine learning and 3D printing, will equip me with the skills needed for a successful academic career in the smart materials and structures field, aligning with my long-term goals.

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More information & hyperlinks

Web resources:	https://cordis.europa.eu/project/id/101153507
Start date:	01-06-2024
End date:	31-05-2026
Total budget - Public funding:	- 187 624,00 Euro

Cordis data

Original description

Mechanical metamaterials play a crucial role in various applications, such as shape morphing, soft robotics, and logic elements. However, the control and guidance of transition waves within these materials have primarily been static. The Meta-SMART project aims to revolutionize this by actively controlling and guiding transition waves using piezoelectric and shape memory polymer-based multimaterial active switches integrated into metamaterial unit cells. Unlike traditional methods, Meta-SMART offers dynamic and reversible control, allowing the metamaterials to adapt autonomously and universally.
To optimize these smart metamaterials, we will implement a machine learning-based inverse design strategy to determine their geometrical parameters. Fabrication will involve 3D printing, followed by experimental testing of transition wave control and guidance. This innovation promises to advance the industrial applications of mechanical metamaterials, offering adaptability to external forces and desired outcomes. Potential uses include controlled energy absorption and dissipation for airflow control in aircraft, selective energy absorption in protective surfaces, and even treatment of Parkinsons disease.
The Meta-SMART project represents a valuable opportunity to expand my expertise in smart materials and structures, enhancing my research profile through hands-on experience in testing and fabrication. Training activities such as TU Delft's teachers' training program, workshops on supervising research projects, and advanced courses in machine learning and 3D printing, will equip me with the skills needed for a successful academic career in the smart materials and structures field, aligning with my long-term goals.