The mechanical and sensory signature of plant-based and animal meat.

Eating less meat is associated with a healthier body and planet. Yet, we remain reluctant to switch to a plant-based diet, largely due to the sensory experience of plant-based meat. Food scientists characterize meat using a double compression test, which only probes one-dimensional behavior.

Machine learning reveals correlations between brain age and mechanics.

Our brain undergoes significant micro- and macroscopic changes throughout its life cycle. It is therefore crucial to understand the effect of aging on the mechanical properties of the brain in order to develop accurate personalized simulations and diagnostic tools. Here we systematically probed the mechanical behavior of n=439 brain tissue samples in tension and compression, in different anatomical regions, for different axon orientations, across five age groups.

Benchmarking physics-informed frameworks for data-driven hyperelasticity.

Data-driven methods have changed the way we understand and model materials. However, while providing unmatched flexibility, these methods have limitations such as reduced capacity to extrapolate, overfitting, and violation of physics constraints. Recently, frameworks that automatically satisfy these requirements have been proposed.

Automated model discovery for muscle using constitutive recurrent neural networks.

The stiffness of soft biological tissues not only depends on the applied deformation, but also on the deformation rate. To model this type of behavior, traditional approaches select a specific time-dependent constitutive model and fit its parameters to experimental data. Instead, a new trend now suggests a machine-learning based approach that simultaneously discovers both the best model and best parameters to explain given data.

Automated model discovery for human brain using Constitutive Artificial Neural Networks.

The brain is our softest and most vulnerable organ, and understanding its physics is a challenging but significant task. Throughout the past decade, numerous competing models have emerged to characterize its response to mechanical loading. However, selecting the best constitutive model remains a heuristic process that strongly depends on user experience and personal preference.