Objective
Advanced functional devices require integration of distinct materials (polymers, ceramics, metals) with different properties to achieve high performance in aerospace, biomedicine, electronic, and automotive. A major structural challenge is associated with localized (mechanical, thermal, electrical) stresses due to property mismatch at different scales, thus causing premature malfunction and failure. Research has focussed on compositional or structural material gradients (in at least one spatial direction) to enable fabrication of in-one body parts (mostly inorganics) with exceptional properties. Examples at rather macroscale include AlGaAs with graded bandgap for solar cells, or Al2O3/Ti with graded mechanical stiffness for bioimplants. However, in light of miniaturization technology, there is a need to translate this concept to nanomaterials. The EVA project aims to establish scientific principles to design and fabricate pioneering organic-inorganic 2D layered nanomaterials with functional gradients and continuous interfaces. My approach to designing such innovative nanomaterials is based on their compositional engineering by using correlations to perform an extended mapping of combinations and properties. I will explore self-assembly techniques in solution and translate them into automated processes to hierarchically build robust components with nm-layered thicknesses and mechanical and optoelectronic gradients. EVA will also demonstrate their use as advanced interfaces for soft bio-tissue coupling and flexible lighting nanosystems, providing answers from the nanoscale to key drivers in these fields: reliability, robustness, and durability. Through this interdisciplinary approach (physics, chemistry, mechanics, biology, and materials science), the envisioned atomically designed hybrids will be a hallmark for frontiers in fields such as energy, health, robotics, and digital technologies.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural scienceschemical sciencespolymer sciences
- engineering and technologynanotechnologynano-materials
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringrobotics
- engineering and technologymaterials engineeringceramics
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Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
16163 Genova
Italy