In the Soft Matter Mechanics lab, we study the relationship between structure and behavior of soft materials, which include polymers, biopolymers, hydrogels and biologically active materials such as cells. For this, we take a multi-scale approach (see figure below) where we decompose a microstructure into its components and analyse the effect of each of these parts on the macroscopic response (elasticity, rheology, adhesion or fracture resistance) of a material. This is achieved via the development of analytical (statistical mechanics & continuum mechanics) and computational approaches (finite element, discrete networks and particle methods), that are integrated with experimental data (see figure below). Results from this work has a wide range of practical applications in the design of smart polymers to be used in medicine, soft robotics and industrial applications, with a focus on the themes highlighted below.

Multiscale soft matter

Multiscale methodology for the study of soft and active materials.

Mechanics, adhesion and fracture of dynamic polymers.

Dynamic polymers are made of molecular networks with transient connections, which makes then visco-elastic, self-healing and potentially recyclable. While omnipresent in biology, their synthetic counterparts have only been recently made in labs (such as vitrimers or covalent adaptable networks for instance). Due to their high energy dissipation, dynamic polymers can exhibit controllable flow and elasticity, exceptional toughness and self-healing properties. We study how molecular architecture and dynamics can be tuned to tame the mechanical response of these wild materials. We now focus on several aspect of their response:

  1. Competition between flow and fracture in dynamic networks. This phenomenon, that is still poorly understood is at the origin of cavitation and fracture in dynamic polymer, and thus at the origin of their resistance to fracture. We aim to elucidate the mechanisms at play and identify molecular networks (multiple networks, hybrid networks, ...) that yield polymers and gels with high fracture toughness.This work is in collaboration with the Cai group (UCSD), with dynamic polymers based on living exchange reactions of disulfide bonds.
  2. Dynamic liquid crystal elastomers.  Number of biological materials are made of a combination of rigid filaments, linked by flexible chains. Inspired by the structure of fungi cell walls and muscles, we study the time-dependent actuation patterns (helical/extensional) of these networks. We seek applications into actuators whose motion is controlled by a dynamic molecular structure that can be reprogrammed over time. This work is in collaboration with the Cai group (UCSD) using disulfide liquid crystal elastomer as a model system and with the Bruns group (CU Boulder) using polyrotaxane gels. 
  3. Failure and fracture in adhesives. We study the complex mechanisms and pattern formation during the failure of adhesives on soft and rigid substrates. This work, in collaboration with 3M corporation aims to develop smart adhesives under various conditions.

dynamic polymers

Adaptive scaffold materials

Bio-printing and tissue engineering is based on the development of high precision polymers that, when seeded with cells, can drive the developement of healthy tissues and organs. These materials should therefore behave as fluids during their injection to a defect, (such as a bone fracture or a cartilage defect) but subsequentely act as temporary scaffolds that support the development of a functional tissue. As there are many scientific challenges in creating such materials, our objective is to generate a fundamental knowledge of their mechanical and dynamical requirements. We do so by pursuing both practical and fundamental questions:

  1. Degradable hydrogel scaffolds for tissue engineering. In close collaboration with tissue engineers from the Bryant group (CU Boulder), we study the chemo-mechanics PEG hydrogel for use as temporary scaffolds to regrow cartilage in patients with osteoarthritis. For this, we develop computational models of cell-seeded hydrogels that locally degrade to make place for new tissue development. We use the model to identify the type of hydrogel structure and dynamics that enables long-term tissue growth (and scaffold disapperance) with continuous mechanical integrity. 
  2. Mechanics of self-deployable scaffolds in nature. Fire ants are ant colonies that are able to quickly assemble and disassemble load-bearing scaffolds by connecting their own bodies to form a structural network that is analogous to dynamic polymers. We use a combination of experimental and computational methods to identify the rules by which these adaptive scaffolds are constructed. Results from this research will inspire the next generation of active polymers that can assist tissue reconstruction in our body.


Cell mechanics

Cells are known to change their mechanical and physical properties upon maturation and disease. The ability to easily and quickly detect these changes over time is a key to early cancer prognosis or increasing the outcome of in-vitro fertilization procedures. Our team develops computational models of the cell cytoskeleton and its surrounding cortical membrane with the aim of detecting its biological state through its “mechanical” signature. The characterization and detection steps are pursued via two approaches:

  1. Assessment of cell mechanics via indentation and pipette aspiration. In collaboration with the metrology group at FEMTO (University of Franche Comte, France), we study the physical changes of human oocytes during maturation. By linking the probability of an oocyte fertility to its mechanical properties (and structural changes), the model will be used to adequately screen and select optimal cells for in-vitro fecondation. 
  2. Detection of abnormal cells (or virus) via their mechanical signature. Abnormal cells (such as cancerous cells in the blood) usually exhibits different mechanical properties from their healthy counterpart, but their detection is difficult since screening involve a very large number of cells. High throughput screening can however be acheived by flowing cells in small pores (or microfluidic devices) by pressure-driven flow or electrophoresis. As a cell passes through a pore, it generates a change in flow pressure (or electrical signal) that depends on pore shape, cell size and properties which can be detected in real time. We use computational mechanics to link cell mechanics to its signature (see figure below). This work in is collaboration with the membrane science group of John Pellegrino (CU Boulder).