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Completed H2020 European Commission

Programmable dynamics of locally multistable metamaterials

€191.1K EUR

Funder European Commission
Recipient Organization Eidgenoessische Technische Hochschule Zuerich
Country Switzerland
Start Date Apr 06, 2021
End Date Apr 05, 2023
Duration 729 days
Number of Grantees 1
Roles Coordinator
Data Source European Commission
Grant ID 101026226
Grant Description

Metamaterials have gained importance across disciplines, owing to their superior and tailorable characteristics and performance.

Alongside classic metamaterials with optimal properties such as customised stiffness, density, wave dispersion, and energy absorption, reconfigurable metamaterials have recently begun to attract attention. Reconfigurability can be achieved by interconnected multistable elements that possess more than one stable state.

Controlled and cooperative switching of large arrays of such multistable elements leads to dynamic transition events of interest for applications ranging from haptic interfaces and morphing surfaces in 2D to shape-morphing and deployable structures in 3D.

This research will focus on a new class of locally multistable 2D metamaterials of great potential for haptics (capable of conveying static and dynamic tactile sensations), while providing the general theoretical basis and new physics for a myriad of applications in both 2D and 3D.

We consider multistable systems with unprecedented numbers of stable equilibria, leading to highly complex transitional behaviour beyond what has been studied so far and beyond what is tractable by available theories.

This calls for new theoretical modelling, simulation tools, and experimental prototyping for validation, which lay the foundations for the main goal of producing a novel interactive haptic interface. The research is divided into three stages.

The first is model development and system identification to facilitate theoretical and efficient numerical descriptions of the system to be experimentally investigated.

The next stage uses machine-learning to identify target reconfiguration (both static and dynamic) utilising minimal actuation. The final stage estimates the loads introduced into the system using an asymptotic solution of the system’s dynamics.

These constitute a step forward in the research of reconfigurable metamaterials and serve as a basis for countless applications.

All Grantees

Eidgenoessische Technische Hochschule Zuerich

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