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Modeling approaches toward bioinspired dynamic materials

Project description

Unravelling the molecular mechanisms that control material self-assembly

Nature uses self-assembly to build fascinating supramolecular materials, such as microtubules and protein filaments, which can self-heal, reconfigure, adapt or respond to specific stimuli dynamically. Building synthetic (polymeric) supramolecular materials that possess similar bio-inspired properties using the same self-assembly principles holds promise for many applications. However, their rational design requires a detailed understanding of the molecular mechanisms that control the self-assembly process, which is typically very difficult to achieve experimentally. The EU-funded DYNAPOL project will shed more light on the molecular origin of the bio-inspired behaviour of these materials using massive multiscale modelling, advanced simulations and machine learning. Research results will lead to fundamental models for the rational design of artificial dynamic materials with controllable bio-inspired properties.

Objective

Nature uses self-assembly to build fascinating supramolecular materials, such as microtubules and protein filaments, that can self-heal, reconfigure, adapt or respond to specific stimuli in dynamic way. Building synthetic (polymeric) supramolecular materials possessing similar bioinspired properties via the same self-assembly principles is interesting for many applications. But their rational design requires a detailed comprehension of the molecular determinants controlling the assembly (structure, dynamics and properties) that is typically very difficult to reach experimentally.
The aim of this project is to obtain structure-dynamics-property relationships to learn how to control the dynamic bioinspired properties of supramolecular polymers. I propose to unravel the molecular origin of the bioinspired behavior through massive multiscale modeling, advanced simulations and machine learning. First, we will develop ad hoc molecular models to study monomer assembly and the supramolecular structure of various types of self-assembled materials on multiple scales. Second, using advanced simulation approaches we will characterize the supramolecular dynamics of these materials (dynamic exchange of monomers) at high (submolecular) resolution. We will then study bioinspired properties such as the ability of various supramolecular materials to self-heal, adapt or reconfigure dynamically in response to specific stimuli. Our models will be systematically validated by comparison with the experimental evidence from our collaborators. Finally, we will use machine learning approaches to analyze our high-resolution simulations and to identify the key monomer features that control and determine the structure, dynamics and dynamic properties of a supramolecular material (i.e. structure-dynamics-property relationships). This research will produce unprecedented insight and fundamental models for the rational design of artificial dynamic materials with controllable bioinspired properties.

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Coordinator

POLITECNICO DI TORINO
Net EU contribution
€ 1 999 623,00
Address
Corso duca degli abruzzi 24
10129 Torino
Italy

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Region
Nord-Ovest Piemonte Torino
Activity type
Higher or Secondary Education Establishments
Links
Other funding
€ 0,00

Beneficiaries (2)