SUMMARY

The sense of smell is critical to a number of animals, from moths all the way to the largest mammal on land, the elephant. Despite these animals ranging across eight orders of magnitude in body mass, there are commonalities in their methods for bringing odor molecules to their sensors. Understanding the olfaction of animals can also inspire the design of autonomous smelling machines, which are currently limited in their speed and sensitivity. Most previous work on olfaction has focused on the neuroscience of animal olfaction or the algorithms involved in processing data from machine olfaction. In this dissertation, we focus on the fluid mechanics of olfaction. We used a combined experimental and theoretical approach, with particular emphasis on building machines that can mimic the olfaction of animals. We show that many animals have a hierarchical structure to their olfaction systems, either antenna or nasal cavities, that increase their surface area to improve the chance of odor deposition. Animals optimize their olfaction with behaviors varying from sniffing to angling their antenna obliquely to the wind. Both methods slow down the air near the sensing surfaces, which increases the number of molecules that can deposit by diffusion.