To reduce the environmental and/or the energetic impact of vehicles, a favored method is to decrease the mass of prime materials used to build them, that being done without hindering their mechanical performances. In this field, the use of mechanical metamaterials has been a major breakthrough. These metamaterials, generally created using additive manufacturing techniques, have a microscopic truss structure. They are porous by design, and thus very lightweight, and the distribution of their microscopic beams or tubes (i.e. their architecture) can be chosen to make them as stiff as possible [2-4], making them choice candidates for high technology applications where the rigidity-density ratio is paramount, such as aerospatial research (https://en.wikipedia.org/wiki/Metallic_microlattice).

For the most part however, metamaterials that have been designed up to now present periodical architectures. As a consequence, their mechanical behavior is inherently anisotropic, which makes them difficult to model using material mechanics conventional approaches, and strongly limits their usage in various possible fields of applications [5,6]. In recent works, we have developped a new class of microlattice metamaterials with a random spatial distribution of beams, generated with a combination of random close packing and Delaunay triangulation algorithm then 3D-manufactured [7]. These metamaterials show an isotropic mechanical behavior, and their stiffness-density ratio reaches the theoretical limit for porous materials [8]. They are neverheless still fragile and subject to fracture and yielding, and we are currently studying the consequences of structure heterogeneities on their mechanical performances.

1. 1. 1. 1. 1. 1. 1. 1. 1. T. M. Tillotson et L. W. Hrubesh, Journal Non-Crystalline Solids 145, 1992

                        2. T. A. Schaedler et al., Science 334, 2011 

                        3. L. R. Mezaet et al., Proceedings of the Natural Academy of Sciences 112, 2015

                        4. X. Zheng et al., Science 344, 2014

                        5. Shivakumar I. Ranganathan and Martin Ostoja-Starzewski, Physical Review Letters 101, 2008 

                        6. R. Perez and P. Gumbsch., Physical Review Letters 84, 2000

                        7. A. Montiel et al. Method for producing an amorphous architecture of the micro-lattice type formed of micro-beams connected together by nodes, patent number 2025020922

                        8. G. Gurtner and M. Durand., Proceedings of the Royal Society A 470, 2014

Due to the multiscale structure of the tongue and palate and crossmodal interactions, food texture cannot be interpreted solely using simple mechanical parameters such as the elastic modulus or the viscosity. In the case of soy-based beverages, and other food colloids, important texture descriptors are graininess, creaminess, and astringency. These properties are influenced by product rheology and tribology [1-3], which depend on the structure of the suspensions [4,5].

Blended soy-cow beverages aim at improving the taste and texture compared to soy beverages. These products are solid suspensions in an oil/water emulsion, whose overall stability depends on the proportion of the different fats and proteins in solution. We study the morphology of such drinks while varying the type of fat in the emulsion. We link these morphologies to rheological and tribological properties measured on a biomimetic surface developed in the group, as well as to sensory profiling.

1. 1. 1. 1. 1. 1. 1. 1. 1. A Sarkar et al., Food Hydrocolloids 117, 2021, DOI: 10.1016/j.foodhyd.2021.106635

                        2. K Liu et al., Food Hydrocolloids, 44, 2015, DOI: 10.1016/j.foodhyd.2014.09.034

                        3. L Laguna et al., Food & Function, 8, 2017, 563, DOI: 10.1039/c6fo01010e

                        4. E Imai et al., Journal of Texture Studies 25, 1997, 3, DOI: 10.1111/j.1745-4603.1997.tb00116.x

                        5. L Engelen et al., Physiology & Behavior 86, 2005, 1-2, DOI: 10.1016/j.physbeh.2005.06.022

My PhD project focuses on systems that we call "solid emulsions", in between emulsions and reinforced composites. They are polymer emulsions whose continuous phase is crosslinked in order to obtain a dispersion of liquid droplets within a solid elastic matrix. Much in the same way that emulsions show unexpected flow properties such as an elastic modulus arising from the mix of two liquids, which is directly dependent on the different phases, the aim of my solid emulsions is to create a composite whose rheology can be easily tuned. In particular, I aim at decoupling the storage and loss moduli (or simply put, the elasticity and viscosity of the composite) with regards to the mixing parameters.

Such a finely tunable system would be interesting, between other applications, in the medicine field to create casts that could allow slow movements in order for instance to wash the body under, but could solidify in an instant to protect against shocks with a shear-thickening dispersed phase.

To carry out this project, I am finding various methods to generate stable and reproducible samples, and proceed with characterization of both their structure through mostly microscopy techniques, and of their mechanical performances through rheology, tensile and adhesion tests.

The problem of inclusion systems has been an issue of interest for soft matter scientists for over five decades, here is a bit of literature to go further:

1. J. F. Palierne, Rheologica Acta, vol. 29, no 3, p. 204‑214, 1990

2. M. Krieger et T. J. Dougherty, Transactions of the Society of Rheology, vol. 3, no 1, p. 137‑152, 1959

3. Mahaut et al., 2008, Journal of Rheology, 52, 287

4. R. W. Style, R. Tutika, J. Y. Kim, M. D. Bartlett, Advanced Functional Materials, 2020, 31

Droplet microfluidics allows for precise experiments on small volumes, which makes it a choice candidate for single cell experiment. In order to study several parameters on a single cell, which is to say to practice so called multi-omnic experiments, an interesting idea is to use tweezers to displace cells from one microreactor (i.e. a droplet containing one reactive) to another. I was formulating microgels containing magnetic nanoparticles on which cells could be grafted, and thus which could be used with magnetic tweezers in a microfluidic apparatus.

The difficulty of this internship resided in the need for a sufficient magnetic response from the microgels, which was especially complex to achieve in only a three months internship. By the end of the spring I had found a possible way to magnetize the gel and was about to do some characterization of the magnetic field when we went into lockdown due to COVID and I had to stop all my experiments.

Under cyclic fatigue, i.e. the repeated use of a material, elastomers tend to break at a critical stress that is much lower than under monotonous loading. Furthermore, in the presence of a pre-existing crack of sufficient length, the crack propagation rate of materials of similar toughness may differ by orders of magnitude for the same applied energy release rate. Hence, different dissipation mechanisms are at play during cyclic loading. 

Double network elastomers have been engineered to resist fatigue fracture better. Their filler network controls the maximal extensibility and elasticity, and the crosslinking acts as sacrificial bonds which introduce purely elastic dissipation in the material. This makes them good model to study elastic dissipation under cyclic fatigue.
During my internship, I was studying several samples of double network methylacrylate elastomers with different crosslinking concentration in the filler network.

The experiments consisted in choosing the ideal conditions to work under to observe only elastic dissipation and no heating or rate dependency of the material, by going above the glass transition temperature, using DSC and uniaxial traction, then obtaining the critical tear stress under monotonous loading and finally doing several fatigue experiments at different fractions of that critical stress to obtain the crack propagation rate in pre-notched samples. To explain the crack propagation rate results, I also studied the samples in confocal microscopy, thanks to a mechanophore marker.

Isotactic polypropylene pipes are semi-crystalline. They are extruded through a die and solidified in their shape by spraying room-temperature water on the outside of the pipe. This leads to a temperature gradient within the wall of the pipe which as a consequence leads to a crystallization rate gradient within that wall. It has been observed that pipes could show different mechanical properties depending notably on the extrusion throughput, and there was a need to understand where those different performances came from in order to better control the production of plastic materials.

My internship consisted on characterizing the microstructure of several pipe samples made under different conditions, using DSC to get the crystallized fraction, and WAXD and SAXS to obtain the polymorphism of the crystallized parts as well as the orientation of the spherulites. A second part of that internship consisted in comparing the structure results to mechanical performance benchmarks to explain the behavior of the pipes, kicking off my interest in the link between microstructure and macro behavior of soft materials.