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| Url | https://cimne.com/sgp/rtd/Project.aspx?id=991 | ||
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| Acronym | POTENTIAL | ||
| Project title | ComPutatiOnal Tools to Enable the desigN of smarT soft materIALs | ||
| Reference | PID2022-141957OB-C21 | ||
| Principal investigator |
Javier BONET CARBONELL - jbonet@cimne.upc.edu
Alberto GARCIA GONZALEZ - berto.garcia@upc.edu |
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| Start date | 01/09/2023 | End date | 31/08/2026 |
| Coordinator | CIMNE | ||
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| Program | P.E. para Impulsar la Investigación Científico-Técnica y su Transferencia | Call | Proyectos Generación de Conocimiento 2022 |
| Subprogram | Subprograma Estatal de Generación de Conocimiento | Category | Nacional |
| Funding body(ies) | MICINN | Grant | $157,500.00 |
| Abstract | The discovery, design, and manufacturing of new soft smart materials such as Electro Active Polymers (EAPs) and Magneto Active Polymers (MAPs), has been reported to be essential for Europes productivity and competitiveness, for businesses of all sizes and across all sectors of the economy. If the EU is to become a true geopolitical actor, it cannot shy away from this challenge. In this vein, the Spanish Science, Technology, and Innovation Strategy (EECTI) 2021-2027 identifies the discovery and design of new composite materials, smart and multifunctional materials and metamaterials as part of the strategic research line "Digital World, Industry, Space, Defense". Specifically, (1) In-silico/In-Lab active metamaterial characterisation, (2) high-fidelity computational modelling and (3) the use of 4D printing, have been identified as three key enablers to address some of the six Grand Challenges faced by Europe, as part of the new Industry 4.0 initiative. Specifically, novel soft-active metamaterials are seen as being instrumental in leading the creation of groundbreaking advancements in five highly transformative sectors: (1) Soft Robotics, (2) Energy harvesters, (3) Data-Science Engineering, (4) Optimum soft-active control for Zero Emissions, (5) Accurate and fast biomedical Drug Delivery. Innovation in these areas of science and technology cannot be individually achieved through either trial-and-error experimental testing, due to the challenging environments in which some of these phenomena take place (e.g., soft robots operating in radioactive environments or novel drug delivery systems embedded within a human body) or via traditional computational techniques (not equipped to take advantage of Big Data). The seminal "2015-2035 NASA Roadmap Report" states that innovation can only be accomplished through 3D prototyped data-driven digital twins capable of generating high-fidelity simulations based on realistic in-lab multi-physics laws. Thus, it is imperative to exploit (1) high-fidelity computational models assisted by 3D printing (and in-lab experiments) and (2) cutting-edge data-driven assimilation techniques, in order to develop new disruptive soft-active metamaterials and methods which can ultimately drive the creation of innovative solutions in the above five sectors. Meeting these challenges, POTENTIAL puts together transversal tools such as Machine Learning and Data Science, optimization, uncertainty quantification and advanced multiphysic & multiscale simulation into an open-source virtual environment that truly aid the design of smart composites and structures based on multifunctional soft metamaterials. The project POTENTIAL is ambitious due to its multi-disciplinarity across different scientific fields, namely, (1) Continuum mechanics, (2) Computational Mechanics, (3) Applied Mathematics, (4) Material discovery and applications. Due to the cross-cutting nature of POTENTIAL, scientific impact can be expected in, at least, two of the strategic research lines of the strategic sector Digital world, Industry, Space, Defense identified in EECTI 2021-207, namely, (1) Modelling, mathematical analysis and new mathematical solutions for science and technology, (2) New materials and manufacturing techniques. | ||
| Proyecto PID2022-141957OB-C21 financiado por MICIU/AEI/10.13039/501100011033/ FEDER, UE | |||