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Rational Design of Soft Hierarchical Materials with Responsive Functionalities: Machine learning Soft Matter to create Soft Machines

Descrizione del progetto

Ingegneria in silicio di materiali morbidi intelligenti

La capacità di progettare razionalmente materiali morbidi reattivi e di controllarne l’autoassemblaggio su scala nanometrica aprirebbe la strada a una vasta gamma di applicazioni, dai sensori e la somministrazione dei farmaci ai rivestimenti intelligenti e ai nanoreattori. I microgel sono da tempo oggetto di intense attività di ricerca e sviluppo per applicazioni di questo genere in quanto rispondono ai cambiamenti nei parametri ambientali a livello locale, quali temperatura, pH o campi forti, con una variazione del loro rigonfiamento. Il progetto SoftML, finanziato dall’UE, sta applicando modelli computazionali e l’apprendimento automatico allo studio di nanoparticelle accoppiate con microgel, aggiungendo un ulteriore livello di complessità a materiali già di per sé complessi. Una migliore comprensione delle dinamiche multiscala sosterrà la progettazione razionale di materiali morbidi reattivi per numerose importanti applicazioni.

Obiettivo

Nature displays fascinating examples of self-assembled materials that reconfigure and respond to external stimuli, e.g. chameleons change color for camouflage, pine cones release seeds upon a change in humidity. Advances in colloid synthesis have resulted in a diversity of self-assembled nanostructures with interesting functional properties. These nanostructures are however passive!
The aim of this project is to explore the new physics that emerges when static nanostructures are elastically coupled to a soft elastic matrix or hydrogel, e.g. nanoparticles with (cross-linked) ligands, core-shell microgel particles. These hydrogels can be actuated by pH, temperature, light, resulting in a (de)swelling of the gel and a reconfiguration of the nanostructure.
Reconfigurable dynamic materials are interesting for applications, but their rational design remains a major challenge as it requires a detailed comprehension of the highly non-trivial coordination of dynamic behaviors of materials across different time and length scales.
Using extensive simulations, coarse-graining and machine learning, I propose to unravel the microscopic origin of the structural and dynamic behavior of soft reconfigurable materials. I will build coarse-grained models at multiple levels to study the structure and properties of these soft materials. I will then investigate the dynamics and shape transformation kinetics of the nanostructure and hydrogel upon actuation.
The final goal is to reverse-engineer using evolutionary algorithms new classes of soft responsive materials from the atomic scale by designing colloids that self-assemble at the mesoscale into large-scale structures, to the macroscopic scale by tailoring the shape-morphing properties.
This research will produce unprecedented insight, novel simulation methods, and fundamental models for the rational design of soft responsive materials that arise from the hierarchical assembly of structures and their dynamic behaviors across scales.

Meccanismo di finanziamento

ERC-ADG - Advanced Grant

Istituzione ospitante

UNIVERSITEIT UTRECHT
Contribution nette de l'UE
€ 2 499 918,75
Indirizzo
HEIDELBERGLAAN 8
3584 CS Utrecht
Paesi Bassi

Mostra sulla mappa

Regione
West-Nederland Utrecht Utrecht
Tipo di attività
Higher or Secondary Education Establishments
Collegamenti
Costo totale
€ 2 499 918,75

Beneficiari (1)