Innovating Works

M4MID

Financiado
Toward Desirable Metal Organic Framework Mixed Matrix Materials through Machine...
Toward Desirable Metal Organic Framework Mixed Matrix Materials through Machine learning guided Interface Design Metal Organic Framework Mixed Matrix Materials (M4s) are prototyped for many applications such as separating membranes, drug delivery systems and fire-safe plastics. Like all composites, the premise of M4s is to achieve greater pr... Metal Organic Framework Mixed Matrix Materials (M4s) are prototyped for many applications such as separating membranes, drug delivery systems and fire-safe plastics. Like all composites, the premise of M4s is to achieve greater properties than those of their isolated components. Yet, the interface between the components determines whether the synergy between the components is achieved or the overall performance is diminished due to their incompatibility. In principle, the interface can be designed by selection and chemical modification of the components involved. However, in practice such design is a very challenging endeavor. Atomistic simulations can predict the structure of the interface, from which the component compatibility may be inferred. Similarly, mechanical testing of the composites may reveal some qualitative characteristics of the interface. Nevertheless, the throughput of these approaches is insufficient to screen the design space for the optimal M4s for various applications. This project aims at developing the capability to computationally design M4s with good mechanical properties. By employing machine learning techniques, we will be able predict the properties of the interface in a high-throughput manner. Similarly, our multi-scale models will establish quantitative relationships between the interfaces and the mechanical properties of the composites, which can be verified experimentally. To achieve these objectives, the Researcher will be provided training-through-research in high-throughput atomistic simulation workflows, material informatics and machine learning for material discovery as well as homogenization techniques and finite element approaches for multi-scale modeling. Moreover, this project will give the Researcher an opportunity to apply her expertise to explore the area of composite design in both basic science and industry-oriented perspective actively undertaken by IMDEA Material Institute. ver más
31/05/2025
181K€
Duración del proyecto: 35 meses Fecha Inicio: 2022-06-30
Fecha Fin: 2025-05-31

Línea de financiación: concedida

El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2022-06-30
Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:
Presupuesto El presupuesto total del proyecto asciende a 181K€
Líder del proyecto
IMDEA MATERIALES No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico TRL 4-5 9M