In Journal of the mechanical behavior of biomedical materials ; h5-index 50.0
Articular cartilage is a poroviscoelastic (PVE) material with remarkable resistance to fracture and fatigue failure. Cartilage failure mechanisms and material properties that govern failure are incompletely understood. Because cartilage is partially comprised of negatively charged glycosaminoglycans, altering solvent osmolarity can influence PVE relaxations. Therefore, this study aims to use osmolarity as a tool to provide additional data to interpret the role of PVE relaxations and identify cartilage failure regimes. Cartilage fracture was induced using a 100 μm radius spheroconical indenter at controlled displacement rates under three different osmolarity solvents. Secondarily, contact pressure (CP) and strain energy density (SED) were estimated to cluster data into two failure regimes with an expectation maximization algorithm. Critical displacement, critical load, critical time, and critical work to fracture increased with increasing osmolarity at a slow displacement rate whereas no significant effect was observed at a fast displacement rate. Clustering provided two distinct failure regimes, with regime (I) at lower normalized thickness (contact radius divided by sample thickness), and regime (II) at higher normalized thickness. Varied CP and SED in regime (I) suggest that failure in the regime is strain-governed. Constant CP and SED in regime (II) suggests that failure in the regime is dominantly governed by stress. These regimes can be interpreted as ductile versus brittle, or using a pressurized fragmentation interpretation. These findings demonstrated fundamental failure properties and postulate failure regimes for articular cartilage.
Chawla Dipul, Eriten Melih, Henak Corinne R
2022-Sep-22
Cartilage fracture, Clustering, Contact pressure, Machine learning, Microindentation, Osmolarity, Strain energy density
