PhD position: auto organisation and mechanical properties of self-healing composite gels

New generation of self-healing hydrogels composed of nanoparticles incorporated into a 3D bio-polymeric matrix (see figure) are revolutionising medical implants technologies. However, the microscopic mechanisms controlling their selfassembly and at the origin of their mechanical properties remains poorly understood, which hinders a technological breakthrough.
This PhD research programme aims at lifting this lock by combining complementary expertise of 2 laboratories in Grenoble: (i) cutting-edge computational techniques through large scale coarse-grained molecular dynamics simulations and experimental investigations of the mechanical behavior of heterogeneous materials at the laboratory 3SR;
(ii) physico-chemical formulation as well as structural characterisation of hydrogels at CERMAV using NMR spectroscopy, Dynamic Light Scattering and Transmission electron microscopy.

The goal of the PhD is to elucidate the following questions:
• How does the kinetics of the self-assembly sculpt the complex spatial organisation of the micro-structure for composite gels ?
• What are the microscopic mechanisms governing their toughening under mechanical loads ?
• What are the impacts of the NPs spatio-temporal organisation and polymers-nanoparticle bond dynamics on their self-healing abilities ?

The successful candidate will benefit from the international outreach of the Université Grenoble Alpes. The core of the thesis will be on computational modeling at the laboratory Soils, Solids, Structures, Risks in the “CoMHet” team gathering renowned experts in the physics and mechanics of divided media, soft architectured and bio-mimetic materials. In parallel, the PhD student will also contribute to experiments at the CERMAV, a fundamental research CNRS laboratory which has internationally recognized expertise in the controlled chemical modification of natural carbohydrate polymers, their assembly in functional materials and their physico-chemical characterisations.
Requests for thesis grant funding submitted and expertise in progress.

Starting date: November 2021 for a period of 3 years.

Candidates with academic backgrounds in statistical physics, soft matter or physico-chemistry are expected.
Specific skills in numerical modeling will be strongly appreciated. Additional knowledge in polymer physics and colloidal materials will be interestingly examined.

Interested candidates should send their CV, a cover letter and official transcripts of the last two years before
2021, May the 21st to Mehdi Bouzid.