Summary
Metamaterials with anomalous and counter-intuitive multiphysics behaviours have been developed during the last two decades to help communication systems, sensing and robotics. Paradigmatic developments in artificial intelligence, Digital Twin approaches and additive manufacturing are pushing the design and production of metamaterials also towards the development artificial equivalent of synapsis and programmability. These advanced metamaterial concepts are however fossil-based and tend to make use of materials with a high carbon footprint and heavy life cycle costs in terms of emissions and environmental sustainability. Sensing/actuation mechanisms are also innate in natural plant fibres, spider silk strands and enzymatic systems, and involve saturation, hygromorphism, piezoelectricity and controlled hysteresis that could provide similar synaptic behaviours. Programmable memory properties could also be mechanically created in solid matter, and similar mnemonic-type architectures abound in natural fibres and related composites. While neurogenesis in electromagnetic metamaterials is at early stages of development, no neuroactive mechanical metamaterial concept and design based on biobased materials has been developed so far. The project aims at developing this paradigmatic new class of metamaterials. We will explore the use of natural fibre composites, bio-based matrices, spider silk strands, 3D printing of bioblock materials and natural piezoelectricity in wood/cellulose combined with metamaterial architectures to develop artificial bio-based and sustainable surrogates of programmable memory with learning/adaptive behaviours similar to artificial neural networks. These metamaterials will autonomously learn from their past loading history and generate resilience in the structures in which they are embedded. The natural materials will also have low carbon footprint and could be further developed by worldwide R&D communities based on the resources locally available.
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| Web resources: | https://cordis.europa.eu/project/id/101020715 |
| Start date: | 01-10-2021 |
| End date: | 30-09-2026 |
| Total budget - Public funding: | 2 478 140,00 Euro - 2 478 140,00 Euro |
Cordis data
Original description
Metamaterials with anomalous and counter-intuitive multiphysics behaviours have been developed during the last two decades to help communication systems, sensing and robotics. Paradigmatic developments in artificial intelligence, Digital Twin approaches and additive manufacturing are pushing the design and production of metamaterials also towards the development artificial equivalent of synapsis and programmability. These advanced metamaterial concepts are however fossil-based and tend to make use of materials with a high carbon footprint and heavy life cycle costs in terms of emissions and environmental sustainability. Sensing/actuation mechanisms are also innate in natural plant fibres, spider silk strands and enzymatic systems, and involve saturation, hygromorphism, piezoelectricity and controlled hysteresis that could provide similar synaptic behaviours. Programmable memory properties could also be mechanically created in solid matter, and similar mnemonic-type architectures abound in natural fibres and related composites. While neurogenesis in electromagnetic metamaterials is at early stages of development, no neuroactive mechanical metamaterial concept and design based on biobased materials has been developed so far. The project aims at developing this paradigmatic new class of metamaterials. We will explore the use of natural fibre composites, bio-based matrices, spider silk strands, 3D printing of bioblock materials and natural piezoelectricity in wood/cellulose combined with metamaterial architectures to develop artificial bio-based and sustainable surrogates of programmable memory with learning/adaptive behaviours similar to artificial neural networks. These metamaterials will autonomously learn from their past loading history and generate resilience in the structures in which they are embedded. The natural materials will also have low carbon footprint and could be further developed by worldwide R&D communities based on the resources locally available.Status
SIGNEDCall topic
ERC-2020-ADGUpdate Date
27-04-2024
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