Project description
Research investigates 3D liquid foam behaviour
Liquid foams are essential to various industries, including food production and mining, owing to their unique ability to deform and flow under stress. Their behaviour depends on how bubbles rearrange. Yet, unlike 2D foams, the dynamics of 3D foams remain unclear. This makes it hard to predict how they respond to stress, often leading to trial-and-error approaches when engineering their properties. With the support of the Marie Skłodowska-Curie Actions programme, the FOAM 3D project will combine advanced tools: X-ray tomography, simulations, and AI to bridge this gap. It will study how 3D foams behave under stress and use graph neural networks to predict where and when bubble rearrangements occur. Project insights could boost foam design and improve understanding of other materials with similar properties.
Objective
Liquid foams possess distinct structural and mechanical properties, making them essential to various industries ranging from food production to ore flotation. When subjected to shear, foams exhibit complex rheological behaviors: responding elastically to small deformations, plastically to larger ones, and flow with a shear-rate-dependent viscosity once their yield stress is exceeded. These behaviors are governed by local plastic rearrangements of bubbles.
Although much is known about local rearrangements in 2D foams, the understanding of 3D foams remains limited. This knowledge gap hinders accurate predictions of dynamical heterogeneities in plastic rearrangements, often leading to trial-and-error approaches when engineering foam properties for applications. This project aims to bridge that gap by combining X-ray tomographic microscopy with numerical simulations and advanced AI techniques.
I will begin by analyzing data from fast X-ray tomographic microscopy experiments combined with rheological measurements, which simultaneously capture the macroscopic response of 3D foams and the detection of plastic rearrangements at the bubble scale. However, the limited temporal resolution of X-ray tomography necessitates the development of experimentally informed numerical simulations to further explore foam dynamics.
Predicting the occurrence of plastic rearrangements remains a significant challenge. To address this, I will develop graph neural networks (GNNs) capable of predicting the spatiotemporal occurrence of plastic events in foams during a secondment at a company specialized in AI. GNNs have already proven effective in predicting plastic events in glasses, making them an ideal tool for this task.
Since foams are an athermal analog of amorphous solids, insights from this research will be applicable to other yield-stress materials, where the interaction of localized plastic rearrangements is crucial for predicting fracture and flow.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences physical sciences optics microscopy
- engineering and technology materials engineering amorphous solids
You need to log in or register to use this function
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2024-PF-01
See all projects funded under this callCoordinator
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
38058 GRENOBLE
France
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.