MGELS - Machine-learning polymer Gel's ELasticity and Structure

ID Call: HORIZON-MSCA-2022-PF-01 MSCA Postdoctoral Fellowships

Sapienza's role in the project: Host Institution

Supervisor: Emanuela Zaccarelli

Fellow: Susana Marin Aguilar

Department: Physics

Project start date: April 1, 2024

Project end date: March 31, 2026

Abstract:

Responsive soft materials, made of crosslinked polymer networks, have emerged as a promising class of systems. In particular, thermoresponsive hydrogels and microgels are widely used from drug delivery to cell engineering and even art restoration. An important feature of such systems is their internal elasticity, which can be tuned according to their preparation protocol and crosslinker concentration. Despite recent progress in their modeling by means of numerical simulations, there is no way to know a priori their structure and elasticity from only their initial constituents, and hence, extensive exploration of initial parameters through simulations and experiments must be performed. To overcome this difficulty, the proposal MGELS--Machine-learning polymer Gel’s ELasticity and Structure-- will exploit Machine Learning (ML) methods to develop novel tools able to predict structural and elastic properties of hydrogels and microgel particles to design in silico polymer networks with desired features.