Innovating Works

MAGNIFY

Financiado
Decoding the Mechanisms Underlying Metal-Organic Frameworks Self-Assembly
Metal-Organic Frameworks (MOFs) are porous materials with many societally relevant potential applications, such as carbon capture, removal of environmental toxins and drug-delivery. Despite the progress in the field, synthesizing... Metal-Organic Frameworks (MOFs) are porous materials with many societally relevant potential applications, such as carbon capture, removal of environmental toxins and drug-delivery. Despite the progress in the field, synthesizing a MOF currently requires tens to hundreds costly and time-consuming trial-and-error synthesis experiments because our ability to correlate the synthesis conditions with the desired MOF structure is very limited. To overcome this, we need to decode the mechanisms underlying MOF self-assembly, a highly complex non-equilibrium process covering a wide range of time- and length-scales, from the formation of the building units to nucleation and growth. In MAGNIFY, my team and I will develop a multi-scale computational methodology that will decode the mechanisms underlying MOF self-assembly and predict synthesis conditions-structure relationships. This ambitious interdisciplinary project combines state-of-the-art multi-scale modelling techniques (enhanced sampling techniques, ab initio, atomistic and coarse-graining modelling), with machine-learning approaches to data analysis (dimensionality reduction and data clustering techniques) trained on new chemical descriptors. We will develop and validate our models in tandem with synthesis experiments. We will test our methodology by applying it to two central problems in MOF rational design: (i) determining how synthesis conditions (temperature, solvent, reactants, metal-to-ligand ratio, additives) drive the resulting MOF material's topology and point defects, as well as to (ii) tackling the very challenging task of predicting the synthesis conditions for producing brand new MOFs. This high-risk high-gain project will produce a breakthrough in the MOF field by enabling fast and resource-efficient MOF rational design and will open new research avenues in investigating the self-assembly of other materials and other complex processes happening through a large span of time- and length-scales. ver más
30/11/2027
SORBONNE UNIVERSIT...
1M€
Perfil tecnológico estimado
Duración del proyecto: 68 meses Fecha Inicio: 2022-03-14
Fecha Fin: 2027-11-30

Línea de financiación: concedida

El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2022-03-14
Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:
ERC-2021-STG: ERC STARTING GRANTS
Cerrada hace 3 años
Presupuesto El presupuesto total del proyecto asciende a 1M€
Líder del proyecto
SORBONNE UNIVERSITE No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico TRL 4-5