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Abstract The semi‐aquatic North American river otter (Lontra canadensis) has the unique challenge of navigating slippery algae‐coated rocks. Unlike other river otter species, each rear paw of the North American river otter has a series of soft, circular, and keratinized plantar pads similar to the felt pads on the boots of fly fishermen. Surrounding these soft pads is a textured epidermal layer. In this combined experimental and numerical study, we investigate the influence of the plantar pads and surrounding skin on the otter's grip. We filmed an otter walking and performed materials testing and histology on preserved otter paws. We present experiments and numerical modeling of how the otter paw may help evacuate water when contacting the river bed. We hope this study will draw interest into natural amphibious grip mechanisms for use in sports and the military. 

Molecular dynamics at the atomistic scale is increasingly being used to predict material properties and speed up the materials design and development process. However, the accuracy of molecular dynamics predictions is sensitively dependent on the force fields. In the traditional force field calibration process, a specific property, predicted by the model, is compared with the experimental observation and the force field parameters are adjusted to minimize the difference. This leads to the issue that the calibrated force fields are not generic and robust enough to predict different properties. Here, a new calibration method based on multi-objective Bayesian optimization is developed to speed up the development of molecular dynamics force fields that are capable of predicting multiple properties accurately. This is achieved by reducing the number of simulation runs to generate the Pareto front with an efficient sequential sampling strategy. The methodology is demonstrated by generating a new coarse-grained force field for polycaprolactone, where the force field can predict mechanical properties and water diffusion in the polymer.